# UMass Amherst researchers track stroke recovery via wrist sensors in 215 people

- Published: 2026-11-06 18:19 UTC
- Section: Life & Health › Medicine
- Tags: stroke recovery assessment, digital arm performance scale, upper-limb motor rehabilitation, wrist accelerometer data, digital biomarker stroke
- URL: https://realtech.media/news/rt-3ab6ed26c7db0209486a3864_umass_amherst_researchers/

**A digital scale derived from home accelerometer data tracked arm motor recovery with less measurement error than clinic tests.**

![UMass Amherst researchers track stroke recovery via wrist sensors in 215 people](https://sgzwpqqelzmajkcubgkl.supabase.co/storage/v1/object/public/rt-media/2026/11/9659ffd57b1f1766.jpg)
*Earth.com*

Researchers led by the University of Massachusetts Amherst developed a digital metric to assess upper-limb motor recovery after stroke using home accelerometer recordings. According to a study published in Science Translational Medicine, the team analyzed about 23,000 hours of wrist-sensor data collected from 215 participants [1]. The cohort included 75 healthy adults, 61 individuals followed through standard rehabilitation during the first six months after stroke, and 79 chronic stroke survivors monitored over an eight-week therapy period [1].

Existing standard clinical assessments require a specialist to score tasks over roughly 30 minutes, usually before and after a rehabilitation course. The researchers constructed the digital arm performance scale (DAPS) by decomposing continuous upper-limb accelerometer data from naturalistic environments into lower-level movement segments. Key features from straight-line movements of the stroke-affected wrist were extracted and aggregated using a linear mixed-effects model to yield a single continuous score [1].

## Precision and ceiling effects

In the early-stage group followed over 24 weeks, the digital score agreed closely with standard clinical tests, while exhibiting 52 to 58 percent lower measurement error [1]. The metric also differentiated stroke survivors who had reached the maximum possible score on clinical tests from healthy participants, demonstrating responsiveness in ranges where standard tools reach an artificial ceiling [1].

## Potential impact on clinical trials

Power analysis indicated that using this digital biomarker could reduce the required sample size for clinical trials with upper-limb recovery end points by more than 60 percent compared with traditional clinical tests [1]. In a simulation of a robot-assisted therapy trial, an 80 percent probability of confirming treatment efficacy required eight patients per group using standard clinical tests, compared with three patients using the digital metric [1]. In a second simulated trial, the required sample size decreased from 26 patients per group to seven [1]. Further third-party validation on independent datasets and regulatory clearance remain necessary before clinical adoption.

## Sources

1. [Science Translational Medicine](https://doi.org/10.1126/scitranslmed.adw3644)
2. [Earth.com](https://www.earth.com/lifestyle/a-wrist-sensor-worn-at-home-tracked-stroke-recovery-more-precisely-than-clinic-tests)

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Source: RealTech, realtech.media — https://realtech.media/news/rt-3ab6ed26c7db0209486a3864_umass_amherst_researchers/