REN Jiaze
Papers
1
Total Citations
3
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1
About
Jiaze Ren is a researcher focused on rehabilitation engineering and human motion analysis, with a particular emphasis on upper limb function recovery following neurological conditions such as stroke. Ren’s work integrates motion capture technology with surface electromyography (sEMG) to quantitatively assess and predict muscle strength—a critical metric for evaluating rehabilitation progress. In their most-cited study, "Upper limb muscle strength prediction based on motion capture and sEMG data" (2019), Ren developed a method to estimate muscle force output during active exercise, which is considered the optimal approach for upper limb rehabilitation. This contribution addresses the significant burden of dyskinesia in stroke survivors by providing objective, data-driven tools for clinicians to monitor recovery. Although early in their career, with this paper accumulating 3 citations, Ren’s work lays a foundation for integrating wearable sensors and biomechanical modeling into personalized rehabilitation protocols. Their research holds promise for advancing assistive technologies and improving outcomes for patients with motor impairments, highlighting a commitment to bridging engineering and clinical practice.
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