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Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation

Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot... Hindawi Applied Bionics and Biomechanics Volume 2018, Article ID 7647562, 10 pages https://doi.org/10.1155/2018/7647562 Research Article Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation 1 1 1 1 Andrea Chiavenna , Alessandro Scano , Matteo Malosio, Lorenzo Molinari Tosatti, and Franco Molteni Institute of Industrial Technologies and Automation, National Research Council, Milan, Italy Rehabilitation Presidium of Valduce Hospital Villa Beretta, Lecco, Italy Correspondence should be addressed to Andrea Chiavenna; andrea.chiavenna@itia.cnr.it Received 24 November 2017; Revised 27 March 2018; Accepted 15 April 2018; Published 3 June 2018 Academic Editor: Jinsook Roh Copyright © 2018 Andrea Chiavenna et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Exoskeleton devices for upper limb neurorehabilitation are one of the most exploited solutions for the recovery of lost motor functions. By providing weight support, passively compensated exoskeletons allow patients to experience upper limb training. Transparency is a desirable feature of exoskeletons that describes how the device alters free movements or interferes with spontaneous muscle patterns. A pilot study on healthy subjects was conducted to evaluate the feasibility of assessing transparency in the framework of muscle synergies. For such purpose, the LIGHTarm exoskeleton prototype was used. LIGHTarm provides gravity support to the upper limb during the execution of movements in the tridimensional workspace. Surface electromyography was acquired during the execution of three daily life movements (reaching, hand-to-mouth, and hand-to-nape) in three different conditions: free movement, exoskeleton-assisted (without gravity compensation), and exoskeleton-assisted (with gravity compensation) on healthy people. Preliminary results suggest that the muscle synergy framework may provide valuable assessment of user transparency and weight support features of devices aimed at rehabilitation. 1. Introduction in hemiparesis following the stroke event is the lack of strength and motor coordination. Poor motor output of the shoulder joint prevents also the recovery of the distal joints, About 15 millions of people experience a stroke every year as they are not adequately stimulated due to the impossibility worldwide [1], and up to 85% of the survivors suffer from to reach the target of the task and produce purposeful inter- limitations in the activities of daily living (ADLs) because of action with the environment. Assistive devices can promote upper limb motor impairment [2–4]. There are several approaches in rehabilitation practice to reduce motor rehabilitation of reaching movements toward an object, pro- vide assist-as-needed motion paradigms [7, 8], or offer differ- impairment and to improve upper limb functionality after ent levels of engagement for the user [9]. In the literature, it stroke. The need of containing costs, time, and resources devoted to physical and occupational therapy after injury was demonstrated that robotic-based rehabilitation protocols and conventional therapy induce comparable, positive effects represents an opportunity for cost-effective and easy-to-use on patients [10]. The main advantages of robot and assistive devices that can take over some of the supervisory functions devices are performing high therapy doses [11] and provide of therapists. In the last decades, robotic rehabilitation has semi-independent movement, which has been shown to attested as a valuable approach able to provide high- intensity training and increase patient motivation, by assist- increase motivation [12, 13]. Furthermore, robots specifically designed for home rehabilitation allow the chance to ing motor training [5, 6]. However, one of the main issues 2 Applied Bionics and Biomechanics stored activation patterns on which the CNS can rely on continue the rehabilitation in domestic environment. Main drawbacks are high initial costs and the need of an external to execute a large number of different movements [27]. operator for patients’ supervision [10]. To reduce the high This result can be achieved because muscle synergies can be tuned in time and magnitude [28, 29]. cost issue, and to reduce the weight of the system, some devices without actuators have been developed, the so- Muscle synergies have been widely employed in studies called “passive exoskeletons” [14]. Passive devices rely on on healthy people to investigate motor control during ADL springs and counterweights to generate assistive torques. such as upper-limb reaching or walking [28–31]. While The efficacy of passive devices and assisted training in general several studies investigated the coupling between muscle syn- ergies with robot control algorithms [32], only a few works is a matter of debate. However, in the literature, similar ther- apy outcomes were found when comparing actuated and not have analyzed the interaction with a rehabilitation device, actuated robots [15]. In medium/high functionality patients despite the potential of the method in quantifying several especially, therapies based on active and passive exoskeletons aspects such as weight support, muscle pattern alteration, induced comparable improvements on upper limb function and global device transparency. A passive weight support device was used to investigate the effects of different levels [16–18]. One of the main advantages of exoskeleton devices is the of gravity compensation on muscle synergies on a set of possibility to move freely in the workspace and, at the same reaching movements, concluding that spatial synergies are time, to allow reaching and manipulating objects with the only slightly altered and temporal components decrease hand. Some studies underlined the importance of exploration proportionally to the level of support [33]. A recent study employed EMG and muscle synergies for a detailed analysis of the workspace as a key factor for functional recovery [16]. For this reason, since arm elevation is one of the major issues of an upper limb exoskeleton in various interaction condi- for workspace exploration, an antigravity support may be tions [34]. Other studies instead analyzed the effects of a needed. Furthermore, when a high muscle activation is planar end-effector training on muscle synergies in acute required for completing a task, patients may show abnormal poststroke patients [35]. In previous works, the LIGHTarm exoskeleton device muscle patterns, such as the flexion synergy, with remarkable effects on the kinematic of the movement [18]. was presented [36] and characterized in a preliminary study Besides gravity support, another desired feature for exo- while holding static postures and performing dynamic move- ments [37]. The study suggested cautious good results for skeletons is transparency, or backdrivability. The backdriving torque can be defined as the amount of torque T that a gravity compensation; an almost unchanged EMG signal was found when the device was not gravity-compensated, human must apply to the robotic joint in order to perform a user-driven movement. Perfect backdrivability is achieved while reduced EMG activity was observed when compen- if T =0 in all conditions [19]; in such a case, the free move- sated. A more refined EMG analysis might evaluate transpar- ency features as a modification of spatial and temporal ment torque is equal to the torque produced while wearing the device, and no additional muscular work is needed to components of muscle synergies underlying movement. To authors’ knowledge, very rarely EMG-based methods were move the limbs. Transparency can be reduced either by high inertia or low joint backdrivability, caused by frictions or adopted to estimate transparency of robot devices. In this mechanical transmission, by specific configurations of the paper, a method for the quantitative evaluation based on muscle synergies was carried out to explore the possibility device links such as elbow singularity, occurring, for exam- ple, when elbow joint is completely extended and the upper of evaluating user transparency, that is, if the interaction with a passive exoskeleton (the LIGHTarm device) alters muscle arm and the forearm segments are aligned [14, 20, 21]. Transparency is a desirable feature, since a high- synergies spatial and temporal composition, and at what transparent device does not interfere with the process of extent, in respect to free movements. motor learning, allowing patients to experience the effort- error relationship typical of motor-learning processes [22]. 2. Materials and Methods However, in order to be helpful, devices must provide assis- tance, and in such cases, transparency has to be reduced. 2.1. Participants. Three healthy subjects were enrolled in this Few studies in the literature investigated the concept of trans- study (Table 1). Subjects had no previous experience with the parency in the framework of a user-centered perspective, LIGHTarm device. Each subject signed a written informed being the balance between high transparency and assistance consent form before inclusion in the study. The study was crucial in the process of motor relearning [23–25]. conducted in compliance with the Declaration of Helsinki. The framework analysis based on muscle synergies might be a valuable tool for investigating how, and at which 2.2. The LIGHTarm Device. The LIGHTarm device (Figure 1) extent, the device alters motor modules and affects transpar- consists of a hybrid mechanism composed of a serial and a ency. Muscle synergies are defined as a spatial-coordinated parallel kinematic chains. The architecture was conceived to recruitment of a group of muscles elicited by a shared neu- allow physiological movements of the shoulder joint and ral command or specific activation waveforms [26]. The avoid singular configurations of the upper limb, especially muscle synergy framework was developed to analyze the of the elbow joint. The weight support mechanism was hypothesis that the central nervous system (CNS) organizes designed as a combination of two separate mechanical ele- modularly to simplify the production of motor outputs. In ments: a counterweight system supporting the whole arm such a view, muscle synergies represent a small subset of and a spring-based system supporting the elbow joint. The Applied Bionics and Biomechanics 3 (i) Reaching against gravity (RCH, Figure 2(a)): from Table 1: Participants. the starting position, the subject raised the arm at ° ° Subjects 90 of shoulder flexion, 0 of shoulder abduction, ID Age Sex Height Weight and with elbow and the fingers extended. Subject 1 46 M 181 68 (ii) Hand-to-mouth (HTM, Figure 2(b)): from the start- Subject 2 23 M 183 85 ing position, the subject raised the arm and flexed Subject 3 29 M 179 78 the elbow to bring the hand to the mouth. (iii) Hand-to-nape (HTN, Figure 2(c)): from the starting position, the subject raised the arm until the hand architecture was conceived to avoid constriction on the was in contact with the nape. shoulder, especially during abduction when a coupled shoul- The three tasks were executed in three different condi- der elevation occurs [14], and therefore preserve the scapulo- tions: free movement without the exoskeleton (free), with humeral rhythm, which is a key issue in the exoskeleton the exoskeleton without arm weight compensation (not com- design. Thanks to the not-actuated design and simple struc- pensated), and with the exoskeleton with arm weight com- ture, LIGHTarm can be considered an affordable device. pensation (compensated). More detailed description of the design of the device can be found in previous works [36, 37]. 2.5. Muscle Synergy Extraction. EMG and kinematic data The experimenters measured subjects’ anthropometry of were recorded during each set of 12 repetitions. Then, the the arm and the forearm and tuned the LIGHTarm so that first and the last movements were discarded, and only the the shoulder and the elbow of the subjects were aligned with forward phase of each repetition was considered for synergy the exoskeleton joints. Then, a proper counterweight was extraction. Movement phases were detected through kine- added so that the weight of the device (without limb) was matic analysis, applying an automatic phase detector algo- compensated. In this way, the weight of the links anterior rithm based on the velocity of vertical coordinate of the to the parallelogram did not influence the execution of move- wrist marker as a reference for RCH and HTM movements ments. After the tuning procedure, the subject was fastened and on the velocity of vertical coordinate of the elbow marker with the strap pads. The arm compensation was chosen as as a reference for the HTN movement. If the elbow marker the amount of weight required to maintain the arm raised tracking was not available due to exoskeleton obstruction, in the position depicted in Figure 1, tested after the operator the lost frames were reconstructed through the four-marker had passively raised the arm of the subject being tested. Once cluster. Data from retroreflective markers were filtered with weight compensation was defined, the subjects executed all a low-pass, 3rd-order Butterworth filter, with cut-off fre- the tasks in one-single session without taking off the device. quency set at 6 Hz. EMG signals of the eight muscles in the forward phase 2.3. Materials and Measures. EMG signals were recorded at a were filtered (high-pass filtering (50 Hz), full-wave rectifica- sample frequency = 1000 Hz, with an 8-channel EMG acqui- tion, FIR low-pass filtering (cut-off frequency = 20 Hz) [34]) sition system (FreeEMG, BTS, Italy) to evaluate muscular in obtaining the envelope of the signal. EMG data from each activation patterns of the following muscles: deltoids ante- subject and each trial were pooled together in a single- rior, middle, and posterior, upper trapezius, pectoralis major, aggregated matrix, and synergies were extracted using the triceps lateral head, biceps brachii caput longum, and bra- nonnegative matrix factorization (NMF) algorithm [38]. chioradialis of the right limb. Such muscles were chosen since The NMF decomposes the electromyography (EMG) matrix they are mainly involved in upper limb tasks with focus on into the product of two matrices, the first one representing exploration of the workspace. time-invariant, spatial-coded synergies (w ), and the second Kinematics of the right limb was recorded with a 6-TVC one representing time-variant activation commands for each marker-based motion capture system (Smart-D, BTS, Italy). synergy (c ) [31], as in the following: Markers were positioned on C7 and D5 vertebras, acromion, right epicondyle of the elbow, and styloid process of the ulna EMG t = 〠 c w , 1 [38]. The elbow marker was at times not tracked due to the i i i=1 exoskeleton encumbrance. A four-marker cluster, placed on the arm, was used to infer elbow position. where for each of the recorded muscles, EMG t represents the EMG data at time t and N is the total number of extracted 2.4. Motor Tasks. The tasks selected to evaluate the LIGHT- synergies. arm were functional movements usually performed in every- The procedure of synergy extraction was performed by day life. The starting position was the same for every pooling together the EMG envelope matrix of each acquisi- movement; the subject was seated on a chair with the hand tion, including ten repetitions of the motor task for each lying on a cushion positioned on the thigh. The subject per- experimental condition (3 subjects × 3 motor tasks). formed 12 repetitions of each task at a self-selected speed The order of the factorization r was chosen increasingly without pauses between one repetition and the following. from 1 to 8 (maximum number of muscles that characterizes The three movements proposed are listed below: the dimensionality of the problem). For each r, the NMF 4 Applied Bionics and Biomechanics (a) (b) Figure 1: The LIGHTarm exoskeleton: prototype and rendering. algorithm was applied 100 times in order to avoid local min- weight support, transparency may be “decomposed” into ima, and the repetition accounting for the higher variance of two main contributions. At first, a desirable transparency the signal was chosen as the representative of order r. The term is related to weight support. As a consequence of LIGHTarm support, the magnitude of temporal compo- number of synergies was chosen as the minimum r explain- ing at least 0.75 of the total variance of the signal [33]. nents should be reduced, because of the less effort needed For representation purposes, authors ordered synergy to elevate the limb. A second term, instead, deals with the modifications of the spatial synergy composition. It investi- datasets by matching synergies that have a similar functional gates how the motor modules are modified due to the role within a specific gesture. For such reasons, synergy interaction with the device. Since the weight support action datasets were matched at best by considering the Pearson should not alter the spatial composition of motor modules correlation coefficient of the temporal components. After underlying movement, preservation of muscle patterns in the matching procedure, extracted synergies are naturally assisted movements in respect to free ones is considered matched so that they are at best comparable between exper- as an index of the effect of the exoskeleton to preserve imental conditions. unaltered physiological patterns and not interfere with Then, the dataset of extracted spatial synergies was split spontaneous EMG activity. into three subdatasets: the first one comprehended the syn- In summary, coordinated muscle patterns can be evalu- ergies extracted from free movements, the second one ated by considering the difference in the composition of spa- including synergies extracted from noncompensated assisted tial muscle synergies, while weight support features can be movements, and the third one including compensated analyzed by considering the magnitude of the temporal com- movements. A k-means cluster analysis was conducted on ponent associated to each synergy. each of the three datasets, to identify mean spatial synergies Consequently, in this work, the evaluation of user trans- (centroids) for each of the experimental conditions. The parency is split into two components: order of each clustering was selected by considering a tra- deoff between accuracy and synthesis, pondering indexes (1) Mean spatial synergy similarity, investigating if related to clustering quality such as silhouette and Euclid- LIGHTarm alters muscle patterns during dynamic ean distance of synergies from their reference centroid. motion. Finally, each temporal component was coupled to its mean spatial synergy. (2) Weight support features, investigating if LIGHTarm is effectively reducing the magnitude of the temporal 2.6. Outcome Measures: User Transparency. While several components related to spatial synergies. definitions of transparency are given in the literature [24, 25], for passive exoskeletons, the concept of user trans- In order to quantify pattern alteration, the similarity of parency is here introduced. User transparency may be mean spatial synergies is considered. The metrics chosen defined as the alteration of motor modules (here modelled for detecting similarity among mean spatial synergies (cen- as muscle synergies) due to the interaction with an exoskel- troids) were the dot product, which was already used in pre- eton. Alterations may be due to device encumbrance, vious studies as an indicator of synergy similarity [39–41]. A singular configurations, mechanical locks or couplings, or high dot product value corresponds to a good similarity weight support features. In this paper, it is proposed that between the conditions, indicating that the presence of the user transparency can be assessed in the framework of exoskeleton would not influence synergy composition. Dot product values range from 0 (no similarity) to 1 (perfect muscle synergies. For a device that is aimed at producing Applied Bionics and Biomechanics 5 (a) (b) (c) Figure 2: The three motor tasks: (a) reaching, (b) hand-to-mouth, and (c) hand-to-nape. similarity). Dot products were calculated between each For the evaluation of the weight support features, the synergy pair obtained by matching free movements, integral of each mean temporal component (mtc) was calcu- LIGHTarm-assisted movements in compensated set-up, lated as a representative of the magnitude of the activation of and LIGHTarm-assisted movements in noncompensated each spatial synergy. A reduction in the integral value is set-up. evidence of less muscular effort needed to perform the 6 Applied Bionics and Biomechanics Spatial synergies Temporal components Subject 1 Subject 2 Subject 3 Subject 1 Subject 2 Subject 3 −4 Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp ×10 1 5 0.5 −4 ×10 1 5 0.5 −4 ×10 0.5 0 0 −4 ×10 1 5 0.5 0 0 −4 ×10 1 5 0.5 −4 ×10 1 5 0.5 −4 ×10 1 5 0.5 −4 ×10 1 5 0.5 0 0 Tr ap ezius Deltoid anterior Deltoid posterior Biceps Pectoralis Deltoid middle Triceps Brachioradialis Figure 3: Synergy spatial composition and temporal components. No-Comp = not compensated, Comp = compensated, TP = upper trapezius, PM = pectoralis major, DA = deltoid anterior, DM = deltoid middle, DP = deltoid posterior, TRI = triceps brachii, BIC = biceps brachii, BR = brachioradialis. movement. The mtc were calculated for each mean temporal muscle patterns underlying movements are not consistently component as follows: altered. All the values found are above the range of baseline dot products identified in previous studies in the literature f to quantify similarity [39], and therefore, a high (>0.75) or mtc = c t dt, 2 i very high (>0.90) similarity [40] is found in this study among mean spatial patterns. that is, the integral of the mean temporal component associ- 3.3. Weight Support Features. Table 3 reports the mtc computed ated to each mean spatial synergy. for each mean temporal component. For easier visualization, temporal components are graphically reported in Figure 5. 3. Results For each mean spatial synergy, the higher mtc value is found in free movements (except centroid 4, which was not 3.1. Synergy Extraction. Spatial synergy compositions, needed to describe the dataset in free movements). The mtc matched by correlation of temporal components, for each in movements performed with LIGHTarm in not compen- of the considered tasks and subjects, are shown in Figure 3. sated set-up indicate that there is a tendency toward a slight reduction of muscle activity. When LIGHTarm was used in 3.2. Spatial Synergy Alteration. Mean spatial synergies, com- puted with the clustering k-means algorithm, are shown in the compensated set-up, the mtc decreases consistently. Figure 4. Pairwise dot products relative to mean spatial synergy 4. Discussion compositions are shown in Table 2. Dot products between free, not compensated, and com- A detailed review of the insights provided by muscle syner- pensated movements are always >0.80 for all the pairwise gies for the assessment of user transparency is presented in matched mean spatial synergies, indicating that the basic the following sections. Hand-to-nape Hand-to-mouth Reaching Synergy 2 Synergy 1 Synergy 3 Synergy 2 Synergy 1 Synergy 3 Synergy 2 Synergy 1 Activation 2 Activation 1 Activation 3 Activation 2 Activation 1 Activation 3 Activation 2 Activation 1 Applied Bionics and Biomechanics 7 Clusters centroids 0.8 0.6 0.4 0.2 1 2 3 4 0.8 0.6 0.4 0.2 1 2 3 4 0.8 0.6 0.4 0.2 1 2 3 4 Trapezius Deltoid posterior Pectoralis Triceps Deltoid anterior Biceps Deltoid middle Brachioradialis Figure 4: Mean spatial synergies (centroids) for each of the three experimental conditions, matched by similarity. It is possible to notice that the compensated configuration requires the coordination of a spatial synergy, which was not observed in free movements and in not compensated assistance. Table 2: Pairwise dot products of the mean spatial synergies (centroids) in the different experimental conditions. Free = free movements, No- Comp = not compensated, Comp = compensated. n.a. = not available data, / = comparison with the same condition. Centroid 1 Centroid 2 Centroid 3 Centroid 4 Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free / 0.89 0.92 / 0.94 0.95 / 0.88 0.82 / n.a. n.a. No-Comp 0.89 / 0.87 0.94 / 0.93 0.88 / 0.86 n.a. / n.a. Comp 0.92 0.87 / 0.95 0.93 / 0.82 0.86 / n.a. n.a. / Referring to Table 2, it is possible to say that, averagely, Table 3: mtc values related to each mean spatial synergy. good similarity between synergy composition in the different No-Comp = not compensated and Comp = compensated. experimental conditions was found, especially considering Centroid 1 Centroid 2 Centroid 3 Centroid 4 the reference values found in the literature (>0.75 high simi- Free 0.2071 0.1307 0.1854 0 larity, >0.90 very high similarity) [39, 40]. When the similar- ity of synergy compositions is above 0.90, the device is not No-Comp 0.1334 0.1208 0.1502 0 altering the modules underlying movement in a relevant Comp 0.0906 0.0548 0.0960 0.0832 manner. In the specific case of LIGHTarm, when comparing free movement to the ones without weight compensation, high similarity was found when considering the three main 4.1. Spatial Synergy Alteration. In comparison to traditional spatial patterns underlying the considered daily life gestures. methods for EMG analysis, muscle synergies capture spatial On the contrary, the compensated configuration, which is the and temporal features that are shared by groups of coactivating one that should be used for rehabilitation for providing full muscles, which, according to this framework, are controlled weight support, induces relevant modifications of the mean as groups rather than autonomous entities. Consequently, spatial synergies. the muscle synergy approach is particularly suited for evalu- In fact, loss of transparency might be observed in the ating pattern alterations induced at the neural level when emergency of new motor modules (centroid 4). While the interacting with a device. main modules are in general preserved, all subjects had to Comp No-Comp Free 8 Applied Bionics and Biomechanics −4 −4 −4 ×10 Centroid 1 Free ×10 Centroid 2 Free ×10 Centroid 3 Free 5 5 5 4 4 4 3 3 3 2 2 2 1 1 1 0 0 0 050 100 050 100 050 100 (%) (%) (%) Centroid 1 Centroid 2 Centroid 3 −4 −4 −4 ×10 No−Comp ×10 No−Comp ×10 No−Comp 5 5 5 4 4 4 3 3 3 2 2 2 1 1 1 0 0 0 050 100 050 100 050 100 (%) (%) (%) −4 −4 −4 −4 Centroid 1 Comp Centroid 2 Comp Centroid 3 Comp Centroid 4 Comp ×10 ×10 ×10 ×10 5 5 5 5 4 4 4 4 3 3 3 3 2 2 2 2 1 1 1 1 0 0 050 100 050 100 050 100 0 50 100 (%) (%) (%) (%) Figure 5: Mean temporal components related to each mean spatial synergy. Free = free movements, No-Comp = not compensated, Comp = compensated. rely on some trials on an additional synergy, characterized In case of a decrease of the temporal component integrals, the by abnormal triceps activation. This result can be inter- device is inducing an effect of reduced effort, allowing the preted in an excessive gravity compensation imposed on subject to elevate the arm with less EMG activity. In the spe- the upper limb, as at the end of the range of motion the cific case of LIGHTarm, a reduced magnitude is always device was still providing support on the arm, slightly shown between the not compensated and the compensated pushing it upwards. Probably, this effect induced triceps configurations. A magnitude difference can also be noticed compensation, needed to slow the shoulder flexion effect between the free and not compensated configurations, with exerted by the exoskeleton. These observations might be decrement of the integral values in most of the trials. Despite valuable for further tuning of the device or for its partial the counterweight was specifically set only for the compensa- redesign. tion of the weight of the exoskeleton, wearing the device While the sample of subjects is too low for proposing sta- induced an effect on the amount of muscle activation needed tistical analysis for the specific case of LIGHTarm, the to complete the movements. This could be interpreted with a explained methodology proposes valuable insights on muscle nonhomogenous support in the workspace, with a slight coordination while interacting with a device and may help in overcompensation of the shoulder when over 90 of shoulder deducing if a generic exoskeleton may induce modifications flexion as seen in the RCH and HTN and a little resistance to the motor modules underlying movement. In hypothesiz- contribution in the lower part of the workspace that require ing to have a wider sample of subjects, the muscle synergy more muscle activation to achieve the target, as seen in HTM. analysis might provide such valuable insights with statistical All the reported results are preliminary and, due to the confirmation—or denial—of the results. low number of subjects, are not statistically significant. How- ever, they show how the muscle synergy framework might be 4.2. Weight Support Features. For a device like LIGHTarm valuable for assessing the weight support features of an exo- which is aimed at supporting the weight of the limb, the skeleton device. weight support features are a needed “loss of transparency”; the magnitude of temporal components should be reduced 4.3. Implications and Limitations. As proposed in many to allow elevating the limb against gravity with less effort. papers [7, 23], transparency is a key feature that a robotic Weight support features can be evaluated by considering device should have to provide valuable assistance to patients the magnitude of the activation profile of each synergy. In in rehabilitation. While remarkable efforts have been done in the muscle synergy framework, the reduction of magnitude the literature to design devices and controllers for achieving of a module is seen as the reduction of activity of a whole transparency [23, 24, 42], few works have investigated the set of muscles responsible for a specific kinematic movement. potential of a modular description of the neuromuscular Activations Activations Activations Activations Activations Activations Activations Activations Activations Activations Applied Bionics and Biomechanics 9 system in evaluating the properties of a device. In this paper, [3] H. I. Krebs, M. Krams, D. K. 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Leonhardt, “A survey on robotic devices for upper limb tion in the rehabilitation field, even if in a very basic form, rehabilitation,” Journal of NeuroEngineering and Rehabilita- here, it is proposed that muscle synergies may represent a tion, vol. 11, no. 1, p. 3, 2014. very interesting framework for testing transparency. [6] J. M. Veerbeek, A. C. Langbroek-Amersfoort, E. E. H. van This study has several limitations. At first, the number of Wegen, C. G. M. Meskers, and G. Kwakkel, “Effects of robot- enrolled subjects is low and does not allow providing statisti- assisted therapy for the upper limb after stroke: a systematic cal conclusions over LIGHTarm transparency. However, sev- review and meta-analysis,” Neurorehabilitation and Neural eral aspects that might be observed in the framework of Repair, vol. 31, no. 2, pp. 107–121, 2017. muscle synergies have been considered, and their applica- [7] P. Morasso, M. Casadio, P. Giannoni et al., “Desirable features bility to other devices has been discussed. Furthermore, of a “humanoid” robot-therapist,” in 2009 Annual Interna- authors acknowledge that many features of muscle synergies tional Conference of the IEEE Engineering in Medicine and could be examined in more detail. A study design including a Biology Society, pp. 2418–2421, Minneapolis, MN, USA, comprehensive exploration of the workspace would elicit a September 2009. higher variety of motor modules, allowing a detailed map- [8] J. M. Frullo, J. Elinger, A. U. Pehlivan et al., “Effects of assist- ping of motor module alterations. This would allow provid- as-needed upper extremity robotic therapy after incomplete ing a more refined mapping of the repertoire of upper limb spinal cord injury: a parallel-group controlled trial,” Frontiers motor modules when in interaction with the device, rather in Neurorobotics, vol. 11, p. 26, 2017. than simple, task-specific patterns. [9] D. J. Reinkensmeyer, E. T. 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Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation

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Copyright © 2018 Andrea Chiavenna et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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10.1155/2018/7647562
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Hindawi Applied Bionics and Biomechanics Volume 2018, Article ID 7647562, 10 pages https://doi.org/10.1155/2018/7647562 Research Article Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation 1 1 1 1 Andrea Chiavenna , Alessandro Scano , Matteo Malosio, Lorenzo Molinari Tosatti, and Franco Molteni Institute of Industrial Technologies and Automation, National Research Council, Milan, Italy Rehabilitation Presidium of Valduce Hospital Villa Beretta, Lecco, Italy Correspondence should be addressed to Andrea Chiavenna; andrea.chiavenna@itia.cnr.it Received 24 November 2017; Revised 27 March 2018; Accepted 15 April 2018; Published 3 June 2018 Academic Editor: Jinsook Roh Copyright © 2018 Andrea Chiavenna et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Exoskeleton devices for upper limb neurorehabilitation are one of the most exploited solutions for the recovery of lost motor functions. By providing weight support, passively compensated exoskeletons allow patients to experience upper limb training. Transparency is a desirable feature of exoskeletons that describes how the device alters free movements or interferes with spontaneous muscle patterns. A pilot study on healthy subjects was conducted to evaluate the feasibility of assessing transparency in the framework of muscle synergies. For such purpose, the LIGHTarm exoskeleton prototype was used. LIGHTarm provides gravity support to the upper limb during the execution of movements in the tridimensional workspace. Surface electromyography was acquired during the execution of three daily life movements (reaching, hand-to-mouth, and hand-to-nape) in three different conditions: free movement, exoskeleton-assisted (without gravity compensation), and exoskeleton-assisted (with gravity compensation) on healthy people. Preliminary results suggest that the muscle synergy framework may provide valuable assessment of user transparency and weight support features of devices aimed at rehabilitation. 1. Introduction in hemiparesis following the stroke event is the lack of strength and motor coordination. Poor motor output of the shoulder joint prevents also the recovery of the distal joints, About 15 millions of people experience a stroke every year as they are not adequately stimulated due to the impossibility worldwide [1], and up to 85% of the survivors suffer from to reach the target of the task and produce purposeful inter- limitations in the activities of daily living (ADLs) because of action with the environment. Assistive devices can promote upper limb motor impairment [2–4]. There are several approaches in rehabilitation practice to reduce motor rehabilitation of reaching movements toward an object, pro- vide assist-as-needed motion paradigms [7, 8], or offer differ- impairment and to improve upper limb functionality after ent levels of engagement for the user [9]. In the literature, it stroke. The need of containing costs, time, and resources devoted to physical and occupational therapy after injury was demonstrated that robotic-based rehabilitation protocols and conventional therapy induce comparable, positive effects represents an opportunity for cost-effective and easy-to-use on patients [10]. The main advantages of robot and assistive devices that can take over some of the supervisory functions devices are performing high therapy doses [11] and provide of therapists. In the last decades, robotic rehabilitation has semi-independent movement, which has been shown to attested as a valuable approach able to provide high- intensity training and increase patient motivation, by assist- increase motivation [12, 13]. Furthermore, robots specifically designed for home rehabilitation allow the chance to ing motor training [5, 6]. However, one of the main issues 2 Applied Bionics and Biomechanics stored activation patterns on which the CNS can rely on continue the rehabilitation in domestic environment. Main drawbacks are high initial costs and the need of an external to execute a large number of different movements [27]. operator for patients’ supervision [10]. To reduce the high This result can be achieved because muscle synergies can be tuned in time and magnitude [28, 29]. cost issue, and to reduce the weight of the system, some devices without actuators have been developed, the so- Muscle synergies have been widely employed in studies called “passive exoskeletons” [14]. Passive devices rely on on healthy people to investigate motor control during ADL springs and counterweights to generate assistive torques. such as upper-limb reaching or walking [28–31]. While The efficacy of passive devices and assisted training in general several studies investigated the coupling between muscle syn- ergies with robot control algorithms [32], only a few works is a matter of debate. However, in the literature, similar ther- apy outcomes were found when comparing actuated and not have analyzed the interaction with a rehabilitation device, actuated robots [15]. In medium/high functionality patients despite the potential of the method in quantifying several especially, therapies based on active and passive exoskeletons aspects such as weight support, muscle pattern alteration, induced comparable improvements on upper limb function and global device transparency. A passive weight support device was used to investigate the effects of different levels [16–18]. One of the main advantages of exoskeleton devices is the of gravity compensation on muscle synergies on a set of possibility to move freely in the workspace and, at the same reaching movements, concluding that spatial synergies are time, to allow reaching and manipulating objects with the only slightly altered and temporal components decrease hand. Some studies underlined the importance of exploration proportionally to the level of support [33]. A recent study employed EMG and muscle synergies for a detailed analysis of the workspace as a key factor for functional recovery [16]. For this reason, since arm elevation is one of the major issues of an upper limb exoskeleton in various interaction condi- for workspace exploration, an antigravity support may be tions [34]. Other studies instead analyzed the effects of a needed. Furthermore, when a high muscle activation is planar end-effector training on muscle synergies in acute required for completing a task, patients may show abnormal poststroke patients [35]. In previous works, the LIGHTarm exoskeleton device muscle patterns, such as the flexion synergy, with remarkable effects on the kinematic of the movement [18]. was presented [36] and characterized in a preliminary study Besides gravity support, another desired feature for exo- while holding static postures and performing dynamic move- ments [37]. The study suggested cautious good results for skeletons is transparency, or backdrivability. The backdriving torque can be defined as the amount of torque T that a gravity compensation; an almost unchanged EMG signal was found when the device was not gravity-compensated, human must apply to the robotic joint in order to perform a user-driven movement. Perfect backdrivability is achieved while reduced EMG activity was observed when compen- if T =0 in all conditions [19]; in such a case, the free move- sated. A more refined EMG analysis might evaluate transpar- ency features as a modification of spatial and temporal ment torque is equal to the torque produced while wearing the device, and no additional muscular work is needed to components of muscle synergies underlying movement. To authors’ knowledge, very rarely EMG-based methods were move the limbs. Transparency can be reduced either by high inertia or low joint backdrivability, caused by frictions or adopted to estimate transparency of robot devices. In this mechanical transmission, by specific configurations of the paper, a method for the quantitative evaluation based on muscle synergies was carried out to explore the possibility device links such as elbow singularity, occurring, for exam- ple, when elbow joint is completely extended and the upper of evaluating user transparency, that is, if the interaction with a passive exoskeleton (the LIGHTarm device) alters muscle arm and the forearm segments are aligned [14, 20, 21]. Transparency is a desirable feature, since a high- synergies spatial and temporal composition, and at what transparent device does not interfere with the process of extent, in respect to free movements. motor learning, allowing patients to experience the effort- error relationship typical of motor-learning processes [22]. 2. Materials and Methods However, in order to be helpful, devices must provide assis- tance, and in such cases, transparency has to be reduced. 2.1. Participants. Three healthy subjects were enrolled in this Few studies in the literature investigated the concept of trans- study (Table 1). Subjects had no previous experience with the parency in the framework of a user-centered perspective, LIGHTarm device. Each subject signed a written informed being the balance between high transparency and assistance consent form before inclusion in the study. The study was crucial in the process of motor relearning [23–25]. conducted in compliance with the Declaration of Helsinki. The framework analysis based on muscle synergies might be a valuable tool for investigating how, and at which 2.2. The LIGHTarm Device. The LIGHTarm device (Figure 1) extent, the device alters motor modules and affects transpar- consists of a hybrid mechanism composed of a serial and a ency. Muscle synergies are defined as a spatial-coordinated parallel kinematic chains. The architecture was conceived to recruitment of a group of muscles elicited by a shared neu- allow physiological movements of the shoulder joint and ral command or specific activation waveforms [26]. The avoid singular configurations of the upper limb, especially muscle synergy framework was developed to analyze the of the elbow joint. The weight support mechanism was hypothesis that the central nervous system (CNS) organizes designed as a combination of two separate mechanical ele- modularly to simplify the production of motor outputs. In ments: a counterweight system supporting the whole arm such a view, muscle synergies represent a small subset of and a spring-based system supporting the elbow joint. The Applied Bionics and Biomechanics 3 (i) Reaching against gravity (RCH, Figure 2(a)): from Table 1: Participants. the starting position, the subject raised the arm at ° ° Subjects 90 of shoulder flexion, 0 of shoulder abduction, ID Age Sex Height Weight and with elbow and the fingers extended. Subject 1 46 M 181 68 (ii) Hand-to-mouth (HTM, Figure 2(b)): from the start- Subject 2 23 M 183 85 ing position, the subject raised the arm and flexed Subject 3 29 M 179 78 the elbow to bring the hand to the mouth. (iii) Hand-to-nape (HTN, Figure 2(c)): from the starting position, the subject raised the arm until the hand architecture was conceived to avoid constriction on the was in contact with the nape. shoulder, especially during abduction when a coupled shoul- The three tasks were executed in three different condi- der elevation occurs [14], and therefore preserve the scapulo- tions: free movement without the exoskeleton (free), with humeral rhythm, which is a key issue in the exoskeleton the exoskeleton without arm weight compensation (not com- design. Thanks to the not-actuated design and simple struc- pensated), and with the exoskeleton with arm weight com- ture, LIGHTarm can be considered an affordable device. pensation (compensated). More detailed description of the design of the device can be found in previous works [36, 37]. 2.5. Muscle Synergy Extraction. EMG and kinematic data The experimenters measured subjects’ anthropometry of were recorded during each set of 12 repetitions. Then, the the arm and the forearm and tuned the LIGHTarm so that first and the last movements were discarded, and only the the shoulder and the elbow of the subjects were aligned with forward phase of each repetition was considered for synergy the exoskeleton joints. Then, a proper counterweight was extraction. Movement phases were detected through kine- added so that the weight of the device (without limb) was matic analysis, applying an automatic phase detector algo- compensated. In this way, the weight of the links anterior rithm based on the velocity of vertical coordinate of the to the parallelogram did not influence the execution of move- wrist marker as a reference for RCH and HTM movements ments. After the tuning procedure, the subject was fastened and on the velocity of vertical coordinate of the elbow marker with the strap pads. The arm compensation was chosen as as a reference for the HTN movement. If the elbow marker the amount of weight required to maintain the arm raised tracking was not available due to exoskeleton obstruction, in the position depicted in Figure 1, tested after the operator the lost frames were reconstructed through the four-marker had passively raised the arm of the subject being tested. Once cluster. Data from retroreflective markers were filtered with weight compensation was defined, the subjects executed all a low-pass, 3rd-order Butterworth filter, with cut-off fre- the tasks in one-single session without taking off the device. quency set at 6 Hz. EMG signals of the eight muscles in the forward phase 2.3. Materials and Measures. EMG signals were recorded at a were filtered (high-pass filtering (50 Hz), full-wave rectifica- sample frequency = 1000 Hz, with an 8-channel EMG acqui- tion, FIR low-pass filtering (cut-off frequency = 20 Hz) [34]) sition system (FreeEMG, BTS, Italy) to evaluate muscular in obtaining the envelope of the signal. EMG data from each activation patterns of the following muscles: deltoids ante- subject and each trial were pooled together in a single- rior, middle, and posterior, upper trapezius, pectoralis major, aggregated matrix, and synergies were extracted using the triceps lateral head, biceps brachii caput longum, and bra- nonnegative matrix factorization (NMF) algorithm [38]. chioradialis of the right limb. Such muscles were chosen since The NMF decomposes the electromyography (EMG) matrix they are mainly involved in upper limb tasks with focus on into the product of two matrices, the first one representing exploration of the workspace. time-invariant, spatial-coded synergies (w ), and the second Kinematics of the right limb was recorded with a 6-TVC one representing time-variant activation commands for each marker-based motion capture system (Smart-D, BTS, Italy). synergy (c ) [31], as in the following: Markers were positioned on C7 and D5 vertebras, acromion, right epicondyle of the elbow, and styloid process of the ulna EMG t = 〠 c w , 1 [38]. The elbow marker was at times not tracked due to the i i i=1 exoskeleton encumbrance. A four-marker cluster, placed on the arm, was used to infer elbow position. where for each of the recorded muscles, EMG t represents the EMG data at time t and N is the total number of extracted 2.4. Motor Tasks. The tasks selected to evaluate the LIGHT- synergies. arm were functional movements usually performed in every- The procedure of synergy extraction was performed by day life. The starting position was the same for every pooling together the EMG envelope matrix of each acquisi- movement; the subject was seated on a chair with the hand tion, including ten repetitions of the motor task for each lying on a cushion positioned on the thigh. The subject per- experimental condition (3 subjects × 3 motor tasks). formed 12 repetitions of each task at a self-selected speed The order of the factorization r was chosen increasingly without pauses between one repetition and the following. from 1 to 8 (maximum number of muscles that characterizes The three movements proposed are listed below: the dimensionality of the problem). For each r, the NMF 4 Applied Bionics and Biomechanics (a) (b) Figure 1: The LIGHTarm exoskeleton: prototype and rendering. algorithm was applied 100 times in order to avoid local min- weight support, transparency may be “decomposed” into ima, and the repetition accounting for the higher variance of two main contributions. At first, a desirable transparency the signal was chosen as the representative of order r. The term is related to weight support. As a consequence of LIGHTarm support, the magnitude of temporal compo- number of synergies was chosen as the minimum r explain- ing at least 0.75 of the total variance of the signal [33]. nents should be reduced, because of the less effort needed For representation purposes, authors ordered synergy to elevate the limb. A second term, instead, deals with the modifications of the spatial synergy composition. It investi- datasets by matching synergies that have a similar functional gates how the motor modules are modified due to the role within a specific gesture. For such reasons, synergy interaction with the device. Since the weight support action datasets were matched at best by considering the Pearson should not alter the spatial composition of motor modules correlation coefficient of the temporal components. After underlying movement, preservation of muscle patterns in the matching procedure, extracted synergies are naturally assisted movements in respect to free ones is considered matched so that they are at best comparable between exper- as an index of the effect of the exoskeleton to preserve imental conditions. unaltered physiological patterns and not interfere with Then, the dataset of extracted spatial synergies was split spontaneous EMG activity. into three subdatasets: the first one comprehended the syn- In summary, coordinated muscle patterns can be evalu- ergies extracted from free movements, the second one ated by considering the difference in the composition of spa- including synergies extracted from noncompensated assisted tial muscle synergies, while weight support features can be movements, and the third one including compensated analyzed by considering the magnitude of the temporal com- movements. A k-means cluster analysis was conducted on ponent associated to each synergy. each of the three datasets, to identify mean spatial synergies Consequently, in this work, the evaluation of user trans- (centroids) for each of the experimental conditions. The parency is split into two components: order of each clustering was selected by considering a tra- deoff between accuracy and synthesis, pondering indexes (1) Mean spatial synergy similarity, investigating if related to clustering quality such as silhouette and Euclid- LIGHTarm alters muscle patterns during dynamic ean distance of synergies from their reference centroid. motion. Finally, each temporal component was coupled to its mean spatial synergy. (2) Weight support features, investigating if LIGHTarm is effectively reducing the magnitude of the temporal 2.6. Outcome Measures: User Transparency. While several components related to spatial synergies. definitions of transparency are given in the literature [24, 25], for passive exoskeletons, the concept of user trans- In order to quantify pattern alteration, the similarity of parency is here introduced. User transparency may be mean spatial synergies is considered. The metrics chosen defined as the alteration of motor modules (here modelled for detecting similarity among mean spatial synergies (cen- as muscle synergies) due to the interaction with an exoskel- troids) were the dot product, which was already used in pre- eton. Alterations may be due to device encumbrance, vious studies as an indicator of synergy similarity [39–41]. A singular configurations, mechanical locks or couplings, or high dot product value corresponds to a good similarity weight support features. In this paper, it is proposed that between the conditions, indicating that the presence of the user transparency can be assessed in the framework of exoskeleton would not influence synergy composition. Dot product values range from 0 (no similarity) to 1 (perfect muscle synergies. For a device that is aimed at producing Applied Bionics and Biomechanics 5 (a) (b) (c) Figure 2: The three motor tasks: (a) reaching, (b) hand-to-mouth, and (c) hand-to-nape. similarity). Dot products were calculated between each For the evaluation of the weight support features, the synergy pair obtained by matching free movements, integral of each mean temporal component (mtc) was calcu- LIGHTarm-assisted movements in compensated set-up, lated as a representative of the magnitude of the activation of and LIGHTarm-assisted movements in noncompensated each spatial synergy. A reduction in the integral value is set-up. evidence of less muscular effort needed to perform the 6 Applied Bionics and Biomechanics Spatial synergies Temporal components Subject 1 Subject 2 Subject 3 Subject 1 Subject 2 Subject 3 −4 Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp ×10 1 5 0.5 −4 ×10 1 5 0.5 −4 ×10 0.5 0 0 −4 ×10 1 5 0.5 0 0 −4 ×10 1 5 0.5 −4 ×10 1 5 0.5 −4 ×10 1 5 0.5 −4 ×10 1 5 0.5 0 0 Tr ap ezius Deltoid anterior Deltoid posterior Biceps Pectoralis Deltoid middle Triceps Brachioradialis Figure 3: Synergy spatial composition and temporal components. No-Comp = not compensated, Comp = compensated, TP = upper trapezius, PM = pectoralis major, DA = deltoid anterior, DM = deltoid middle, DP = deltoid posterior, TRI = triceps brachii, BIC = biceps brachii, BR = brachioradialis. movement. The mtc were calculated for each mean temporal muscle patterns underlying movements are not consistently component as follows: altered. All the values found are above the range of baseline dot products identified in previous studies in the literature f to quantify similarity [39], and therefore, a high (>0.75) or mtc = c t dt, 2 i very high (>0.90) similarity [40] is found in this study among mean spatial patterns. that is, the integral of the mean temporal component associ- 3.3. Weight Support Features. Table 3 reports the mtc computed ated to each mean spatial synergy. for each mean temporal component. For easier visualization, temporal components are graphically reported in Figure 5. 3. Results For each mean spatial synergy, the higher mtc value is found in free movements (except centroid 4, which was not 3.1. Synergy Extraction. Spatial synergy compositions, needed to describe the dataset in free movements). The mtc matched by correlation of temporal components, for each in movements performed with LIGHTarm in not compen- of the considered tasks and subjects, are shown in Figure 3. sated set-up indicate that there is a tendency toward a slight reduction of muscle activity. When LIGHTarm was used in 3.2. Spatial Synergy Alteration. Mean spatial synergies, com- puted with the clustering k-means algorithm, are shown in the compensated set-up, the mtc decreases consistently. Figure 4. Pairwise dot products relative to mean spatial synergy 4. Discussion compositions are shown in Table 2. Dot products between free, not compensated, and com- A detailed review of the insights provided by muscle syner- pensated movements are always >0.80 for all the pairwise gies for the assessment of user transparency is presented in matched mean spatial synergies, indicating that the basic the following sections. Hand-to-nape Hand-to-mouth Reaching Synergy 2 Synergy 1 Synergy 3 Synergy 2 Synergy 1 Synergy 3 Synergy 2 Synergy 1 Activation 2 Activation 1 Activation 3 Activation 2 Activation 1 Activation 3 Activation 2 Activation 1 Applied Bionics and Biomechanics 7 Clusters centroids 0.8 0.6 0.4 0.2 1 2 3 4 0.8 0.6 0.4 0.2 1 2 3 4 0.8 0.6 0.4 0.2 1 2 3 4 Trapezius Deltoid posterior Pectoralis Triceps Deltoid anterior Biceps Deltoid middle Brachioradialis Figure 4: Mean spatial synergies (centroids) for each of the three experimental conditions, matched by similarity. It is possible to notice that the compensated configuration requires the coordination of a spatial synergy, which was not observed in free movements and in not compensated assistance. Table 2: Pairwise dot products of the mean spatial synergies (centroids) in the different experimental conditions. Free = free movements, No- Comp = not compensated, Comp = compensated. n.a. = not available data, / = comparison with the same condition. Centroid 1 Centroid 2 Centroid 3 Centroid 4 Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free No-Comp Comp Free / 0.89 0.92 / 0.94 0.95 / 0.88 0.82 / n.a. n.a. No-Comp 0.89 / 0.87 0.94 / 0.93 0.88 / 0.86 n.a. / n.a. Comp 0.92 0.87 / 0.95 0.93 / 0.82 0.86 / n.a. n.a. / Referring to Table 2, it is possible to say that, averagely, Table 3: mtc values related to each mean spatial synergy. good similarity between synergy composition in the different No-Comp = not compensated and Comp = compensated. experimental conditions was found, especially considering Centroid 1 Centroid 2 Centroid 3 Centroid 4 the reference values found in the literature (>0.75 high simi- Free 0.2071 0.1307 0.1854 0 larity, >0.90 very high similarity) [39, 40]. When the similar- ity of synergy compositions is above 0.90, the device is not No-Comp 0.1334 0.1208 0.1502 0 altering the modules underlying movement in a relevant Comp 0.0906 0.0548 0.0960 0.0832 manner. In the specific case of LIGHTarm, when comparing free movement to the ones without weight compensation, high similarity was found when considering the three main 4.1. Spatial Synergy Alteration. In comparison to traditional spatial patterns underlying the considered daily life gestures. methods for EMG analysis, muscle synergies capture spatial On the contrary, the compensated configuration, which is the and temporal features that are shared by groups of coactivating one that should be used for rehabilitation for providing full muscles, which, according to this framework, are controlled weight support, induces relevant modifications of the mean as groups rather than autonomous entities. Consequently, spatial synergies. the muscle synergy approach is particularly suited for evalu- In fact, loss of transparency might be observed in the ating pattern alterations induced at the neural level when emergency of new motor modules (centroid 4). While the interacting with a device. main modules are in general preserved, all subjects had to Comp No-Comp Free 8 Applied Bionics and Biomechanics −4 −4 −4 ×10 Centroid 1 Free ×10 Centroid 2 Free ×10 Centroid 3 Free 5 5 5 4 4 4 3 3 3 2 2 2 1 1 1 0 0 0 050 100 050 100 050 100 (%) (%) (%) Centroid 1 Centroid 2 Centroid 3 −4 −4 −4 ×10 No−Comp ×10 No−Comp ×10 No−Comp 5 5 5 4 4 4 3 3 3 2 2 2 1 1 1 0 0 0 050 100 050 100 050 100 (%) (%) (%) −4 −4 −4 −4 Centroid 1 Comp Centroid 2 Comp Centroid 3 Comp Centroid 4 Comp ×10 ×10 ×10 ×10 5 5 5 5 4 4 4 4 3 3 3 3 2 2 2 2 1 1 1 1 0 0 050 100 050 100 050 100 0 50 100 (%) (%) (%) (%) Figure 5: Mean temporal components related to each mean spatial synergy. Free = free movements, No-Comp = not compensated, Comp = compensated. rely on some trials on an additional synergy, characterized In case of a decrease of the temporal component integrals, the by abnormal triceps activation. This result can be inter- device is inducing an effect of reduced effort, allowing the preted in an excessive gravity compensation imposed on subject to elevate the arm with less EMG activity. In the spe- the upper limb, as at the end of the range of motion the cific case of LIGHTarm, a reduced magnitude is always device was still providing support on the arm, slightly shown between the not compensated and the compensated pushing it upwards. Probably, this effect induced triceps configurations. A magnitude difference can also be noticed compensation, needed to slow the shoulder flexion effect between the free and not compensated configurations, with exerted by the exoskeleton. These observations might be decrement of the integral values in most of the trials. Despite valuable for further tuning of the device or for its partial the counterweight was specifically set only for the compensa- redesign. tion of the weight of the exoskeleton, wearing the device While the sample of subjects is too low for proposing sta- induced an effect on the amount of muscle activation needed tistical analysis for the specific case of LIGHTarm, the to complete the movements. This could be interpreted with a explained methodology proposes valuable insights on muscle nonhomogenous support in the workspace, with a slight coordination while interacting with a device and may help in overcompensation of the shoulder when over 90 of shoulder deducing if a generic exoskeleton may induce modifications flexion as seen in the RCH and HTN and a little resistance to the motor modules underlying movement. In hypothesiz- contribution in the lower part of the workspace that require ing to have a wider sample of subjects, the muscle synergy more muscle activation to achieve the target, as seen in HTM. analysis might provide such valuable insights with statistical All the reported results are preliminary and, due to the confirmation—or denial—of the results. low number of subjects, are not statistically significant. How- ever, they show how the muscle synergy framework might be 4.2. Weight Support Features. For a device like LIGHTarm valuable for assessing the weight support features of an exo- which is aimed at supporting the weight of the limb, the skeleton device. weight support features are a needed “loss of transparency”; the magnitude of temporal components should be reduced 4.3. Implications and Limitations. As proposed in many to allow elevating the limb against gravity with less effort. papers [7, 23], transparency is a key feature that a robotic Weight support features can be evaluated by considering device should have to provide valuable assistance to patients the magnitude of the activation profile of each synergy. In in rehabilitation. While remarkable efforts have been done in the muscle synergy framework, the reduction of magnitude the literature to design devices and controllers for achieving of a module is seen as the reduction of activity of a whole transparency [23, 24, 42], few works have investigated the set of muscles responsible for a specific kinematic movement. potential of a modular description of the neuromuscular Activations Activations Activations Activations Activations Activations Activations Activations Activations Activations Applied Bionics and Biomechanics 9 system in evaluating the properties of a device. In this paper, [3] H. I. Krebs, M. Krams, D. K. Agrafiotis et al., “Robotic measurement of arm movements after stroke establishes it is suggested that muscle synergies may be considered for biomarkers of motor recovery,” Stroke, vol. 45, no. 1, comparing motor modules underlying movement in free pp. 200–204, 2014. movements and robot-assisted ones, providing a user- [4] P. S. Lum, C. Patten, D. Kothari, and R. Yap, “Effects of veloc- centered view of the transparency properties of the device. ity on maximal torque production in poststroke hemiparesis,” While a few other studies suggested [23] or exploited Muscle & Nerve, vol. 30, no. 6, pp. 732–742, 2004. [33–35] the potential of muscle synergies as outcome vari- [5] P. Maciejasz, J. Eschweiler, K. Gerlach-Hahn, A. Jansen-Troy, ables for assessing human-robot or human-device interac- and S. 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