journal article·2025-09-08Open access

Sensor-Based Analysis of Upper Limb Motor Coordination After Stroke: Insights from EMG, ROM, and Motion Data During the Wolf Motor Function Test

Ji-Yong Jung, Jung-Ja Kim

Applied Sciences· Volume 15· Issue 17

Abstract

The Wolf Motor Function Test (WMFT) is widely used to evaluate upper limb motor performance after stroke. However, conventional approaches may overlook domain-specific neuromuscular and kinematic differences during task execution. This study classified WMFT tasks into three functional domains: proximal reaching and transport (PRT), fine motor manipulation (FMM), and gross motor functional control (GMFC). Interlimb differences in muscle activation, joint mobility, and movement amplitude were examined using sensor-based measurements. Twelve individuals with chronic stroke performed 16 WMFT tasks. Surface electromyography (EMG) and inertial measurement units (IMUs) recorded upper limb muscle activity, joint angles, and segmental displacement. Wilcoxon signed-rank tests and Spearman correlations were conducted for each functional domain. Significant asymmetries in EMG, range of motion (ROM), and root mean square (RMS) acceleration were found in PRT and FMM tasks. These results reflect increased proximal muscle activation and reduced distal engagement on the paretic side. GMFC tasks elicited more symmetrical patterns but still showed subtle deficits in distal control. Correlation analyses demonstrated strong interdependencies among neuromuscular and kinematic measures. This finding underscores the integrated nature of compensatory strategies. Categorizing WMFT tasks by functional domain and integrating multimodal sensor analysis revealed nuanced impairment patterns. These patterns were not detectable by conventional observational scoring. These findings support the use of sensor-based, domain-specific assessment to guide individualized rehabilitation strategies. Such approaches may ultimately enhance long-term functional recovery in stroke survivors.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Stroke Rehabilitation and Recovery · Muscle activation and electromyography studies · Motor Control and Adaptation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Division of Biomedical Engineering, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si 54896, Jeonbuk State, Republic of Korea

Research Center of Healthcare & Welfare Instrument for the Aged, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si 54896, Jeonbuk State, Republic of Korea

Funding

National Research Foundation of Korea (NRF)

References (56)

Show source-provided references
1. Motor recovery after stroke: A systematic review10.1016/S1474-4422(09)70150-4 ↗
2. Roby-Brami, A., Jarrasse, N., and Parry, R. (2021). Impairment and compensation in dexterous upper-limb function after stroke. From the direct consequences of pyramidal tract lesions to behavioral involvement of both upper-limbs in daily activities. Front. Hum. Neurosci., 15.10.3389/fnhum.2021.662006 ↗
3. Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms10.1186/s12984-019-0609-6 ↗
4. Upper limb assessment with inertial measurement units according to the international classification of functioning in stroke: A systematic review and correlation meta-analysis10.1080/10749357.2023.2197278 ↗
5. Repnik, E., Puh, U., Goljar, N., Munih, M., and Mihelj, M. (2018). Using inertial measurement units and electromyography to quantify movement during action research arm test execution. Sensors, 18.10.3390/s18092767 ↗
6. Observation of amounts of movement practice provided during stroke rehabilitation10.1016/j.apmr.2009.04.005 ↗
7. Systematic review on kinematic assessments of upper limb movements after stroke10.1161/STROKEAHA.118.023531 ↗
8. Development of a compensation-aware virtual rehabilitation system for upper extremity rehabilitation in community-dwelling older adults with stroke10.1186/s12984-023-01183-y ↗
9. Responsiveness of kinematic and clinical measures of upper-limb motor function after stroke: A systematic review and meta-analysis10.1016/j.rehab.2020.02.005 ↗
10. Konieczny, M., Pakosz, P., Domaszewski, P., Błaszczyszyn, M., and Kawala-Sterniuk, A. (2022). Analysis of upper limbs target-reaching movement and muscle co-activation in patients with first time stroke for rehabilitation progress monitoring. Appl. Sci., 12.10.3390/app12031551 ↗
11. Quantifying pathological synergies in the upper extremity of stroke subjects with the use of inertial measurement units: A pilot study
12. Quantitative upper limb impairment assessment for stroke rehabilitation: A review10.1109/JSEN.2024.3359811 ↗
13. Sheng, B., Chen, X., Cheng, J., Zhang, Y., Tao, J., and Duan, C. (2024). A novel scoring approach for the Wolf Motor Function Test in stroke survivors using motion-sensing technology and machine learning: A preliminary study. Comput. Methods Programs Biomed., 243.10.1016/j.cmpb.2023.107887 ↗
14. Characterization of stroke-related upper limb motor impairments across various upper limb activities by use of kinematic core set measures10.1186/s12984-021-00979-0 ↗
15. Parnandi, A., Uddin, J., Nilsen, D.M., and Schambra, H. (2019). Pragmatic classification of movement primitives for stroke rehabilitation. arXiv.
16. Zaidi, K.F., and Harris-Love, M. (2023, January 24–27). A novel Procrustes analysis method to quantify multi-joint coordination of the upper extremity after stroke. Proceedings of the 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney, Australia.10.1109/EMBC40787.2023.10341023 ↗
17. Assessment of movement quality in robot-assisted upper limb rehabilitation after stroke: A review10.1186/1743-0003-11-137 ↗
18. Kinematic analysis of the upper extremity after stroke—How far have we reached and what have we grasped?10.1179/1743288X15Y.0000000002 ↗
19. Upper extremity kinematics: Development of a quantitative measure of impairment severity and dissimilarity after stroke10.7717/peerj.16374 ↗
20. Goffredo, M., Proietti, S., Pournajaf, S., Galafate, D., Cioeta, M., Le Pera, D., Posteraro, F., and Franceschini, M. (2022). Baseline robot-measured kinematic metrics predict discharge rehabilitation outcomes in individuals with subacute stroke. Front. Bioeng. Biotechnol., 10.10.3389/fbioe.2022.1012544 ↗
21. Hwang, D., Shin, J.H., and Kwon, S. (2021). Kinematic assessment to measure change in impairment during active and active-assisted type of robotic rhhabilitation for patients with stroke. Sensors, 21.10.3390/s21217055 ↗
22. Assessing Wolf motor function test as outcome measure for research in patients after stroke10.1161/01.STR.32.7.1635 ↗
23. The reliability of the wolf motor function test for assessing upper extremity function after stroke10.1053/apmr.2001.23183 ↗
24. Movement therapy induced neural reorganization and motor recovery in stroke: A review10.1016/j.jbmt.2011.01.023 ↗
25. Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review10.1177/1545968307305457 ↗
26. Can the wolf motor function test be streamlined?10.1177/1545968308331141 ↗
27. Smartwatch-based functional assessment for upper extremity impairment after musculoskeletal injuries: A pilot study10.1177/15691861241241775 ↗
28. Measurement structure of the Wolf Motor Function Test: Implications for motor control theory10.1177/1545968310370749 ↗
29. Feldner, H.A., Papazian, C., Peters, K.M., Creutzfeldt, C.J., and Steele, K.M. (2021). Clinical use of surface electromyography to track acute upper extremity muscle recovery after stroke: A descriptive case study of a single patient. Appl. Syst. Innov., 4.10.3390/asi4020032 ↗
30. Liu, J., Kang, S.H., Xu, D., Ren, Y., Lee, S.J., and Zhang, L.Q. (2017). EMG-based continuous and simultaneous estimation of arm kinematics in able-bodied individuals and stroke survivors. Front. Neurosci., 11.10.3389/fnins.2017.00480 ↗
31. Lv, W., Liu, K., Zhou, P., Huang, F., and Lu, Z. (2023). Surface EMG analysis of weakness distribution in upper limb muscles post-stroke. Front. Neurol., 14.10.3389/fneur.2023.1135564 ↗
32. Assessing stroke-induced abnormal muscle coactivation in the upper limb using the surface EMG co-contraction Index: A systematic review10.1016/j.jelekin.2025.102985 ↗
33. Sampling, noise-reduction and amplitude estimation issues in surface electromyography10.1016/S1050-6411(01)00033-5 ↗
34. IMU-based systems for upper limb kinematic analysis in clinical applications: A systematic review10.1109/JSEN.2024.3436532 ↗
35. Fang, Z., Woodford, S., Senanayake, D., and Ackland, D. (2023). Conversion of upper-limb inertial measurement unit data to joint angles: A systematic review. Sensors, 23.10.3390/s23146535 ↗
36. The impact of shoulder abduction loading on volitional hand opening and grasping in chronic hemiparetic stroke10.1177/1545968317697033 ↗
37. The effect of arm weight support on upper limb muscle synergies during reaching movements10.1186/1743-0003-11-22 ↗
38. The effect of force feedback delay on stiffness perception and grip force modulation during tool-mediated interaction with elastic force fields10.1152/jn.00229.2014 ↗
39. Compensatory versus noncompensatory shoulder movements used for reaching in stroke10.1177/1545968315613863 ↗
40. Position-dependent torque coupling and associated muscle activation in the hemiparetic upper extremity10.1007/s00221-006-0637-x ↗
41. Myoelectric pattern identification of stroke survivors using multivariate empirical mode decomposition10.1260/2040-2295.5.3.261 ↗
42. Xie, Q., Sheng, B., Huang, J., Zhang, Q., and Zhang, Y. (2022). A pilot study of compensatory strategies for reach-to-grasp-pen in patients with stroke. Appl. Bionics Biomech., 2022.10.1155/2022/6933043 ↗
43. Pregnolato, G., Severini, G., Maistrello, L., Rimini, D., Lencioni, T., Carpinella, I., Ferrarin, M., Jonsdottir, J., Cheung, V.C., and Turolla, A. Muscle synergy analysis for clinical characterization of upper limb motor recovery after stroke. Arch. Phys. Med. Rehabil., 2025.10.1016/j.apmr.2025.05.019 ↗
44. Phan, T., Nguyen, H., Vermillion, B.C., Kamper, D.G., and Lee, S.W. (2022). Abnormal proximal-distal interactions in upper-limb of stroke survivors during object manipulation: A pilot study. Front. Hum. Neurosci., 16.10.3389/fnhum.2022.1022516 ↗
45. Alterations in upper limb muscles synergy structure in chronic stroke survivors10.1152/jn.00670.2012 ↗
46. Influence of chronic stroke on functional arm reaching: Quantifying deficits in the ipsilesional upper extremity
47. Augmented muscle activation in reaching movements after stroke10.5114/hm.2020.91344 ↗
48. Co-activation of upper limb muscles during reaching in post-stroke subjects: An analysis of the contralesional and ipsilesional limbs10.1016/j.jelekin.2014.04.011 ↗
49. Alterations in muscle networks in the upper extremity of chronic stroke survivors10.1109/TNSRE.2021.3075907 ↗
50. Post-stroke movement disorders: Clinical spectrum, pathogenesis, and management10.4103/0028-3886.314574 ↗
51. Restoring motor functions after stroke: Multiple approaches and opportunities10.1177/1073858417737486 ↗
52. Intensity of task-specific training for functional ability post-stroke: Systematic review and meta-analysis10.1177/02692155251351906 ↗
53. The use of wearable sensors to assess and treat the upper extremity after stroke: A scoping review10.1080/09638288.2021.1957027 ↗
54. Neurotechnology-aided interventions fur upper limb motor rehabilitation in severe chronic stroke10.1093/brain/awz181 ↗
55. Technology-based compensation assessment and detection of upper extremity activities of stroke survivors: Systematic review10.2196/34307 ↗
56. Effectiveness of a sensor-based technology in upper limb motor recovery in post-acute stroke neurorehabilitation: A randomized controlled trial