Technology-aided assessment of functionally relevant sensorimotor impairments in arm and hand of post-stroke individuals

Christoph M Kanzler, Anne Schwarz, Jeremia P O Held, Andreas R Luft, Roger Gassert, Olivier Lambercy, Christoph M Kanzler, Anne Schwarz, Jeremia P O Held, Andreas R Luft, Roger Gassert, Olivier Lambercy

Abstract

Background: Assessing arm and hand sensorimotor impairments that are functionally relevant is essential to optimize the impact of neurorehabilitation interventions. Technology-aided assessments should provide a sensitive and objective characterization of upper limb impairments, but often provide arm weight support and neglect the importance of the hand, thereby questioning their functional relevance. The Virtual Peg Insertion Test (VPIT) addresses these limitations by quantifying arm and hand movements as well as grip forces during a goal-directed manipulation task requiring active lifting of the upper limb against gravity. The aim of this work was to evaluate the ability of the VPIT metrics to characterize arm and hand sensorimotor impairments that are relevant for performing functional tasks.

Methods: Arm and hand sensorimotor impairments were systematically characterized in 30 chronic stroke patients using conventional clinical scales and the VPIT. For the latter, ten previously established kinematic and kinetic core metrics were extracted. The validity and robustness of these metrics was investigated by analyzing their clinimetric properties (test-retest reliability, measurement error, learning effects, concurrent validity).

Results: Twenty-three of the participants, the ones with mild to moderate sensorimotor impairments and without strong cognitive deficits, were able to successfully complete the VPIT protocol (duration 16.6 min). The VPIT metrics detected impairments in arm and hand in 90.0% of the participants, and were sensitive to increased muscle tone and pathological joint coupling. Most importantly, significant moderate to high correlations between conventional scales of activity limitations and the VPIT metrics were found, thereby indicating their functional relevance when grasping and transporting objects, and when performing dexterous finger manipulations. Lastly, the robustness of three out of the ten VPIT core metrics in post-stroke individuals was confirmed.

Conclusions: This work provides evidence that technology-aided assessments requiring goal-directed manipulations without arm weight support can provide an objective, robust, and clinically feasible way to assess functionally relevant sensorimotor impairments in arm and hand in chronic post-stroke individuals with mild to moderate deficits. This allows for a better identification of impairments with high functional relevance and can contribute to optimizing the functional benefits of neurorehabilitation interventions.

Keywords: Digital health metrics; Motor control; Neurological disorders; Upper limb assessment.

Conflict of interest statement

Andreas R. Luft is a scientific advisor to Hocoma AG (Volketswil, Switzerland). The remaining authors have no conflict of interest in the submission of this manuscript.

Figures

Fig. 1
Fig. 1
Concept of the Virtual Peg Insertion Test (VPIT). Visualization of hardware setup (top), extracted movement and grip force data (middle) for one exemplary control (age 36 yrs, male) and post-stroke (age 52 yrs, male, FMA-UE 55, ARAT 52) subject, and the processed impairment profiles (bottom) relying on 10 metrics (M1-M10). M1: log jerk transport. M2: log jerk return. M3: SAL return. M4: path length ratio transport. M5: path length ratio return. M6: velocity max return. M7: jerk peg approach. M8: force peaks transport. M9: force rate SAL transport. M10: force rate SAL hole approach. SAL: spectral arc length
Fig. 2
Fig. 2
Example correlations between impairments (VPIT, Fugl-Meyer Upper Extremity) and activity limitations (Box and Block Test). The relationship of impairments and activity limitations was analyzed with Spearman correlations (ρ). Two pairs (a-b) were chosen for visualization purposes (all results in Table 2). Only data from the most affected side (ρma) and the first testing session was used for the correlation analysis. For both VPIT and conventional scales, triangles represent a cut-offs indicating the presence of sensorimotor impairments (VPIT, Fugl-Meyer Upper Extremity) and activity limitations (Box and Block Test). A slightly stronger relationship was observed between impairments and activity limitations for the VPIT metric than the Fugl-Meyer assessment. **indicates p-value below the Bonferonni corrected significance level. VPIT: Virtual Peg Insertion Test
Fig. 3
Fig. 3
Clinimetric evaluation of the VPIT metrics: example log jerk transport. a) shows the behavior of all subjects across five repetitions of test and retest to visualize potential learning effects. b) informs on test-retest reliability by visualizing the median across those five repetitions for test and retest. The red line indicates the population median for the most affected side, the triangle corresponds to the 95th-percentile of the normative reference population, and shaded gray lines connect data from one subject. c) systematic bias was evaluated using a Bland-Altman plot (start and end of gray bars on the right indicate the 5th- and 95th-percentile). d) intra-subject variability was displayed through the standard deviation (std) within all ten repetitions of each subject. The example metric log jerk transport did not show strong learning effects, had high test-retest reliability, no systematic bias, and low intra-subject variability, therefore being defined as robust. TP: transport

References

    1. Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, O’Flaherty M, Pandey A, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani SS. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Am Heart Assoc. 2019;139(10):e56–e528.
    1. Lawrence ES, Coshall C, Dundas R, Stewart J, Rudd a. G., Howard R, Wolfe CD. Estimates of the prevalence of acute stroke impairments and disability in a multiethnic population, Stroke J Cereb Circ. 2001;32(6):1279–84. doi: 10.1161/01.STR.32.6.1279.
    1. World Health Organization. International classification of functioning, disability and health: ICF. World Health Organ. 2001. 10.4135/9781412950510.n454.
    1. Pollock A, Farmer SE, Brady MC, Langhorne P, Mead GE, Mehrholz J, van Wijck F. Interventions for improving upper limb function after stroke. Cochrane Database Syst Rev. 2014; 11. 10.1002/14651858.cd010820.pub2.
    1. French B, Thomas LH, Coupe J, McMahon NE, Connell L, Harrison J, Sutton CJ, Tishkovskaya S, Watkins CL. Repetitive task training for improving functional ability after stroke. Cochrane Database Syst Rev. 2016; 11. 10.1002/14651858.cd006073.
    1. Carr JH, Shepherd R. Movement Science: Foundations for Physical Therapy in Rehabilitation. Illinois: Aspen Publishers Inc; 1989.
    1. Carr J, Shepherd R. The changing face of neurological rehabilitation. Braz J Phys Therapy. 2006;10(2):147–56. doi: 10.1590/S1413-35552006000200003.
    1. Krakauer JW, Carmichael ST. Cambridge: MIT Press: 2017. p. 1–288.
    1. Alt Murphy M, Resteghini C, Feys P, Lamers I. An overview of systematic reviews on upper extremity outcome measures after stroke, BMC Neurol. 2015;15:29. doi: 10.1186/s12883-015-0292-6.
    1. Burridge J, Alt Murphy M, Buurke J, Feys P, Keller T, Klamroth-Marganska V, Lamers I, McNicholas L, Prange G, Tarkka I, Timmermans A, Hughes A-M. A Systematic Review of International Clinical Guidelines for Rehabilitation of People With Neurological Conditions: What Recommendations Are Made for Upper Limb Assessment? Front Neurol. 2019;10(June):1–14.
    1. Rabadi MH, Rabadi FM. Comparison of the Action Research Arm Test and the Fugl-Meyer Assessment as Measures of Upper-Extremity Motor Weakness After Stroke. Arch Phys Med Rehabil. 2006;87(7):962–6. doi: 10.1016/j.apmr.2006.02.036.
    1. Wei XJ, Tong KY, Hu XL. The responsiveness and correlation between Fugl-Meyer Assessment, Motor Status Scale, and the Action Research Arm Test in chronic stroke with upper-extremity rehabilitation robotic training. Int J Rehabil Res. 2011;34(4):349–56. doi: 10.1097/MRR.0b013e32834d330a.
    1. Hoonhorst MH, Nijland RH, Van Den Berg JS, Emmelot CH, Kollen BJ, Kwakkel G. How Do Fugl-Meyer Arm Motor Scores Relate to Dexterity According to the Action Research Arm Test at 6 Months Poststroke? Arch Phys Med Rehabil. 2015;96(10):1845–9. doi: 10.1016/j.apmr.2015.06.009.
    1. Gladstone DJ, Danells CJ, Black SE. The Fugl-Meyer Assessment of Motor Recovery after Stroke: A Critical Review of Its Measurement Properties. Neurorehabil Neural Repair. 2002;16(3):232–40. doi: 10.1177/154596802401105171.
    1. Hawe RL, Scott SH, Dukelow SP. Taking Proportional Out of Stroke Recovery. Stroke J Cereb Circ. 2018;50(1):204–11. doi: 10.1161/STROKEAHA.118.023006.
    1. Hope TMH, Friston K, Price CJ, Leff AP, Rotshtein P, Bowman H. Recovery after stroke: not so proportional after all?, Brain J Neurol. 2019;142(1):15–22. doi: 10.1093/brain/awy302.
    1. Schwarz A, Kanzler CM, Lambercy O, Luft AR, Veerbeek JM. Systematic review on kinematic assessments of upper limb movements after stroke. Stroke J Cereb Circ. 2019;50(3):718–27. doi: 10.1161/STROKEAHA.118.023531.
    1. Alt Murphy M, Häger CK. Kinematic analysis of the upper extremity after stroke – how far have we reached and what have we grasped? Phys Ther Rev. 2015;20(3):137–55. doi: 10.1179/1743288X15Y.0000000002.
    1. Ellis MD, Lan Y, Yao J, Dewald JPAA. Robotic quantification of upper extremity loss of independent joint control or flexion synergy in individuals with hemiparetic stroke: a review of paradigms addressing the effects of shoulder abduction loading. J NeuroEngineering Rehabil. 2016;13(1):95. doi: 10.1186/s12984-016-0203-0.
    1. Coderre AM, Zeid AA, Dukelow SP, Demmer MJ, Moore KD, Demers MJ, Bretzke H, Herter TM, Glasgow JI, Norman KE, Bagg SD, Scott SH. Assessment of Upper-Limb Sensorimotor Function of Subacute Stroke Patients Using Visually Guided Reaching. Neurorehabil Neural Repair. 2010;24(6):528–41. doi: 10.1177/1545968309356091.
    1. Krebs HI, Krams M, Agrafiotis DK, Di Bernardo A, Chavez JC, Littman GS, Yang E, Byttebier G, Dipietro L, Rykman A, McArthur K, Hajjar K, Lees KR, Volpe BT. Robotic measurement of arm movements after stroke establishes biomarkers of motor recovery. Stroke J Cereb Circ. 2014;45(1):200–4. doi: 10.1161/STROKEAHA.113.002296.
    1. Colombo R, Cusmano I, Sterpi I, Mazzone A, Delconte C, Pisano F. Test-retest reliability of robotic assessment measures for the evaluation of upper limb recovery. IEEE Trans Neural Syst Rehabil Eng. 2014;22(5):1020–9. doi: 10.1109/TNSRE.2014.2306571.
    1. Longhi M, Merlo A, Prati P, Giacobbi M, Mazzoli D. Instrumental indices for upper limb function assessment in stroke patients: A validation study. J NeuroEng Rehabil. 2016;13(1):52. doi: 10.1186/s12984-016-0163-4.
    1. Alt Murphy M, Willén C, Sunnerhagen KS. Movement kinematics during a drinking task are associated with the activity capacity level after stroke. Neurorehabil Neural Repair. 2012;26(9):1106–15. doi: 10.1177/1545968312448234.
    1. Alt Murphy M, Willén C, Sunnerhagen KS. Responsiveness of upper extremity kinematic measures and clinical improvement during the first three months after stroke. Neurorehabil Neural Repair. 2013;27(9):844–53. doi: 10.1177/1545968313491008.
    1. Baak B, Bock O, Dovern A, Saliger J, Karbe H, Weiss PH. Deficits of reach-to-grasp coordination following stroke: Comparison of instructed and natural movements. Neuropsychologia. 2015;77:1–9. doi: 10.1016/j.neuropsychologia.2015.07.018.
    1. Johansson GM, Häger CK. A modified standardized nine hole peg test for valid and reliable kinematic assessment of dexterity post-stroke. J NeuroEng Rehabil. 2019;16(1):8. doi: 10.1186/s12984-019-0479-y.
    1. Gulde P, Hughes CML, Hermsdörfer J. Effects of Stroke on Ipsilesional End-Effector Kinematics in a Multi-Step Activity of Daily Living. Front Hum Neurosci. 2017; 11(February). 10.3389/fnhum.2017.00042.
    1. Allgöwer K, Hermsdörfer J. Fine motor skills predict performance in the Jebsen Taylor Hand Function Test after stroke. Clin Neurophysiol. 2017;128(10):1858–71. doi: 10.1016/j.clinph.2017.07.408.
    1. Shirota C, Balasubramanian S, Melendez-Calderon A. Technology-aided assessments of sensorimotor function: current use, barriers and future directions in the view of different stakeholders. J NeuroEng Rehabil. 2019;16(1):53. doi: 10.1186/s12984-019-0519-7.
    1. Fluet M, Lambercy O, Gassert R. Upper limb assessment using a Virtual Peg Insertion Test. In: Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR): 2011. p. 1–6. 10.1109/icorr.2011.5975348.
    1. Kanzler CM, Rinderknecht MD, Schwarz A, Lamers I, Gagnon C, Held J, Feys P, Luft AR, Gassert R, Lambercy O. A data-driven framework for selecting and validating digital health metrics: use-case in neurological sensorimotor impairments. npj Digit Med. 2020;3:80. doi: 10.1038/s41746-020-0286-7.
    1. Gagnon C, Lavoie C, Lessard I, Mathieu J, Brais B, Bouchard JP, Fluet MC, Gassert R, Lambercy O. The Virtual Peg Insertion Test as an assessment of upper limb coordination in ARSACS patients: A pilot study. J Neurol Sci. 2014;347(1-2):341–4. doi: 10.1016/j.jns.2014.09.032.
    1. Hofmann P, Held J, Gassert R, Lambercy O. Proceedings of the International Convention on Rehabilitation Engineering & Assistive Technology (i-CREATe) Singapore: Singapore Therapeutic, Assistive & Rehabilitative Technologies (START) Centre; 2016. Assessment of movement patterns in stroke patients: a case study with the Virtual Peg Insertion Test.
    1. Tobler-Ammann BC, De Bruin ED, Fluet M-CC, Lambercy O, De Bie RA, Knols RH. Concurrent validity and test-retest reliability of the Virtual Peg Insertion Test to quantify upper limb function in patients with chronic stroke. J NeuroEng Rehabil. 2016;13(1):8. doi: 10.1186/s12984-016-0116-y.
    1. Mathiowetz V, Weber K, Kashman N, Volland G. Adult Norms for the Nine Hole Peg Test of Finger Dexterity. Occup Ther J Res. 1985;5(1):24–38. doi: 10.1177/153944928500500102.
    1. Scott SH. Optimal feedback control and the neural basis of volitional motor control. Nat Rev Neurosci. 2004;5(7):532–46. doi: 10.1038/nrn1427.
    1. Hogan N, Sternad D. Sensitivity of Smoothness Measures to Movement Duration, Amplitude, and Arrests. J Motor Behav. 2009;41(6):529–34. doi: 10.3200/35-09-004-RC.
    1. Balasubramanian S, Melendez-Calderon A, Burdet E. A robust and sensitive metric for quantifying movement smoothness. IEEE Trans Biomed Eng. 2012;59(8):2126–36. doi: 10.1109/TBME.2011.2179545.
    1. Balasubramanian S, Melendez-Calderon A, Roby-Brami A, Burdet E. On the analysis of movement smoothness, J NeuroEng Rehabil. 2015;12(1):112. doi: 10.1186/s12984-015-0090-9.
    1. Cirstea MC, Levin MF. Compensatory strategies for reaching in stroke, Brain J Neurol. 2000;123(5):940–53. doi: 10.1093/brain/123.5.940.
    1. Lang CE, Bland MD, Bailey RR, Schaefer SY, Birkenmeier RL. Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making. J Hand Ther. 2013;26(2):104–15. doi: 10.1016/j.jht.2012.06.005.
    1. Chiti G, Pantoni L. Use of montreal cognitive assessment in patients with stroke. Stroke J Cereb Circ. 2014;45(10):3135–40. doi: 10.1161/STROKEAHA.114.004590.
    1. Bohannon RW, Smith MB. Interrater Reliability of a Modified Ashworth Scale of Muscle Spasticity. Phys Ther. 1987;67(2):206–7. doi: 10.1093/ptj/67.2.206.
    1. Stolk-Hornsveld F, Crow JL, Hendriks EP, van der Baan R, Harmeling-van der Wel BC. The Erasmus MC modifications to the (revised) Nottingham Sensory Assessment: A reliable somatosensory assessment measure for patients with intracranial disorders. Clin Rehabil. 2006;20(2):160–72. doi: 10.1191/0269215506cr932oa.
    1. Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4(4):483–92. doi: 10.1097/00004356-198112000-00001.
    1. Platz T, Pinkowski C, Wijck FV, Kim I. -h., Bella P, Johnson G. Clinical Rehabilitation Reliability and validity of arm function assessment Test, Action Research Arm Test and Box and Block Test : a multicentre study. Clin Rehabil. 2005;19:404–11. doi: 10.1191/0269215505cr832oa.
    1. Oxford Grice K, Vogel KA, Le V, Mitchell A, Muniz S, Vollmer MA. Adult Norms for a Commercially Available Nine Hole Peg Test for Finger Dexterity. Am J Occup Ther. 2003;57(5):570–3. doi: 10.5014/ajot.57.5.570.
    1. Mathiowetz V, Volland G, Kashman N, Weber K. Adult Norms for the Box and Block Test of Manual Dexterity. Am J Occup Ther. 1985;39(6):386–91. doi: 10.5014/ajot.39.6.386.
    1. Schaefer SY, Haaland KY, Sainburg RL. Ipsilesional motor deficits following stroke reflect hemispheric specializations for movement control. Brain J Neurol. 2007;130(8):2146–58. doi: 10.1093/brain/awm145.
    1. Hinkle DE, Wiersma W, Jurs SG. Applied Statistics for the Behavioral Sciences. Boston: Houghton Mifflin; 1988.
    1. de Vet HCW, Terwee CB, Knol DL, Bouter LM. When to use agreement versus reliability measures. J Clin Epidemiol. 2006;59(10):1033–9. doi: 10.1016/j.jclinepi.2005.10.015.
    1. Prinsen CAC, Mokkink LB, Bouter LM, Alonso J, Patrick DL, de Vet HCW, Terwee CB. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1147–57. doi: 10.1007/s11136-018-1798-3.
    1. Pfennings L, Cohen L, Adèr H, Polman C, Lankhorst G, Smits R, Van Der Ploeg H. Exploring differences between subgroups of multiple sclerosis patients in health-related quality of life. J Neurol. 1999;246(7):587–91. doi: 10.1007/s004150050408.
    1. Beckerman H, Roebroeck ME, Lankhorst GJ, Becher JG, Bezemer PD, Verbeek ALM. Smallest real difference, a link between reproducibility and responsiveness. Qual Life Res. 2001;10(7):571–8. doi: 10.1023/A:1013138911638.
    1. Martin Bland J, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;327(8476):307–10. doi: 10.1016/S0140-6736(86)90837-8.
    1. Jones TA. Motor compensation and its effects on neural reorganization after stroke. Nat Rev Neurosci. 2017;18(5):267. doi: 10.1038/nrn.2017.26.
    1. Hussain N, Alt Murphy M, Sunnerhagen KS. Upper Limb Kinematics in Stroke and Healthy Controls Using Target-to-Target Task in Virtual Reality. Front Neurol. 2018;9(3):1–9.
    1. Hussain N, Sunnerhagen KS, Alt Murphy M. End-point kinematics using virtual reality explaining upper limb impairment and activity capacity in stroke. J NeuroEng Rehabil. 2019;16(1):1–9. doi: 10.1186/s12984-019-0551-7.
    1. Tyryshkin K, Coderre AM, Glasgow JI, Herter TM, Bagg SD, Dukelow SP, Scott SH. A robotic object hitting task to quantify sensorimotor impairments in participants with stroke, J NeuroEng Rehabil. 2014;11(1):47. doi: 10.1186/1743-0003-11-47.
    1. Lowrey CR, Jackson CP, Bagg SD, Dukeow SP, Scott SH. A Novel Robotic Task for Assessing Impairments in Bimanual Coordination Post-Stroke. Int J Phys Med Rehabil. 2014; S3(1). 10.4172/2329-9096.s3-002.
    1. Germanotta M, Cruciani A, Pecchioli C, Loreti S, Spedicato A, Meotti M, Mosca R, Speranza G, Cecchi F, Giannarelli G, Padua L, Aprile I. Reliability, validity and discriminant ability of the instrumental indices provided by a novel planar robotic device for upper limb rehabilitation. J NeuroEng Rehabil. 2018;15(1):39. doi: 10.1186/s12984-018-0385-8.
    1. Zariffa J, Myers M, Coahran M, Wang RH, Smallest real differences for robotic measures of upper extremity function after stroke: Implications for tracking recovery. J Rehabil Assist Technol Eng. 2018; 5. 10.1177/2055668318788036.
    1. Kanzler CM, Lamers I, Feys P, Gassert R, Lambercy O. Personalized prediction of rehabilitation outcomes in multiple sclerosis: a proof-of-concept using clinical data, digital health metrics, and machine learning. bioRxiv. 2020:1–27. 10.1101/2020.03.26.010264.
    1. Dewald JPA, Pope PS, Given JD, Buchanan TS, Rymer WZ. Abnormal muscle coactivation patterns during isometric torque generation at the elbow and shoulder in hemiparetic subjects. Brain J Neurol. 1995;118(2):495–510. doi: 10.1093/brain/118.2.495.
    1. Dewald JPA, Beer RF. Abnormal joint torque patterns in the paretic upper limb of subjects with hemiparesis. Muscle Nerve. 2001;24(2):273–83. doi: 10.1002/1097-4598(200102)24:2<273::AID-MUS130>;2-Z.
    1. Sukal TM, Ellis MD, Dewald JPA. Shoulder abduction-induced reductions in reaching work area following hemiparetic stroke: Neuroscientific implications. Exp Brain Res. 2007;183(2):215–23. doi: 10.1007/s00221-007-1029-6.
    1. Mukherjee A, Chakravarty A. Spasticity Mechanisms – for the Clinician. Front Neurol. 2010;1(December):1–10.
    1. Sommerfeld DK, Eek EUB, Svensson AK, Holmqvist LW, Von Arbin MH. Spasticity after Stroke: Its Occurrence and Association with Motor Impairments and Activity Limitations. Stroke J Cereb Circ. 2004;35(1):134–9. doi: 10.1161/01.STR.0000105386.05173.5E.
    1. Dietz V, Sinkjaer T. Spastic movement disorder: impaired reflex function and altered muscle mechanics. Lancet Neurol. 2007;6(8):725–33. doi: 10.1016/S1474-4422(07)70193-X.
    1. Lincoln N, Crow J, Jackson J, Waters G, Adams S, Hodgson P. The unreliability of sensory assessments. Clin Rehabil. 1991;5(4):273–82. doi: 10.1177/026921559100500403.
    1. Bosecker C, Dipietro L, Volpe B, Igo Krebs H. Kinematic Robot-Based Evaluation Scales and Clinical Counterparts to Measure Upper Limb Motor Performance in Patients With Chronic Stroke. Neurorehab Neural Repair. 2010;24(1):62–69. doi: 10.1177/1545968309343214.
    1. Otaka E, Otaka Y, Kasuga S, Nishimoto A, Yamazaki K, Kawakami M, Ushiba J, Liu M. Clinical usefulness and validity of robotic measures of reaching movement in hemiparetic stroke patients, J NeuroEng Rehabil. 2015;12(1):66. doi: 10.1186/s12984-015-0059-8.
    1. Tran VD, Dario P, Mazzoleni S. Kinematic measures for upper limb robot-assisted therapy following stroke and correlations with clinical outcome measures: A review. Med Eng Phys. 2018;53:13–31. doi: 10.1016/j.medengphy.2017.12.005.
    1. Schweighofer N, Wang C, Mottet D, Laffont I, Bakthi K, Reinkensmeyer DJ, Rémy-Néris O. Dissociating motor learning from recovery in exoskeleton training post-stroke. J NeuroEng Rehabil. 2018;15(1):89. doi: 10.1186/s12984-018-0428-1.
    1. Patten C, Kothari D, Whitney J, Lexell J, Lum PS. Reliability and responsiveness of elbow trajectory tracking. J Rehabil Res Dev. 2003;40(6):487. doi: 10.1682/JRRD.2003.11.0487.
    1. Wagner JM, Rhodes JA, Patten C. Reproducibility and Minimal Detectable Change of Three-Dimensional Kinematic Analysis of Reaching Tasks in People With Hemiparesis After Stroke. Phys Ther. 2008;88(5):652–63. doi: 10.2522/ptj.20070255.
    1. Patterson TS, Bishop MD, McGuirk TE, Sethi A, Richards LG. Reliability of upper extremity kinematics while performing different tasks in individuals with stroke. J Motor Behav. 2011;43(2):121–30. doi: 10.1080/00222895.2010.548422.
    1. Colombo R, Sterpi I, Mazzone A, Delconte C, Pisano F. Taking a lesson from patients’ recovery strategies to optimize training during robot-aided rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2012;20(3):276–85. doi: 10.1109/TNSRE.2012.2195679.
    1. Gilliaux M, Lejeune TM, Detrembleur C, Sapin J, Dehez B, Selves C, Stoquart G. Using the robotic device REAplan as a valid, reliable, and sensitive too l to quantify upper limb impairments in stroke patients. J Rehabil Med. 2014;46(2):117–25. doi: 10.2340/16501977-1245.
    1. Simpson LA, Eng JJ. Functional recovery following stroke: Capturing changes in upper-extremity function. Neurorehabil Neural Repair. 2013;27(3):240–50. doi: 10.1177/1545968312461719.
    1. Kanzler CM, Schwarz A, Held J, Luft AR, Gassert R, Lambercy O. Technology-aided assessment of functionally relevant sensorimotor impairments in arm and hand of post-stroke individuals. bioRxiv. 2020. 10.1101/2020.04.16.044719.

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