Neurotremor: A wearable Supportive Device for Supporting Upper Limb Muscle Function
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866914108823044096 |
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| author | Aueawattthanaphisut, Aueaphum Srichaisak, Thanyanee Ieochai, Arissa |
| author_facet | Aueawattthanaphisut, Aueaphum Srichaisak, Thanyanee Ieochai, Arissa |
| contents | A sensor-fused wearable assistance prototype for upper-limb function (triceps brachii and extensor pollicis brevis) is presented. The device integrates surface electromyography (sEMG), an inertial measurement unit (IMU), and flex/force sensors on an M5StickC plus an ESP32-S3 compute hub. Signals are band-pass and notch filtered; features (RMS, MAV, zero-crossings, and 4-12 Hz tremor-band power) are computed in 250 ms windows and fed to an INT8 TensorFlow Lite Micro model. Control commands are bounded by a control-barrier-function safety envelope and delivered within game-based tasks with lightweight personalization. In a pilot technical feasibility evaluation with healthy volunteers (n = 12) performing three ADL-oriented tasks, tremor prominence decreased (Delta TI = -0.092, 95% CI [-0.102, -0.079]), range of motion increased (+12.65%, 95% CI [+8.43, +13.89]), repetitions rose (+2.99 min^-1, 95% CI [+2.61, +3.35]), and the EMG median-frequency slope became less negative (Delta = +0.100 Hz/min, 95% CI [+0.083, +0.127]). The sensing-to-assist loop ran at 100 Hz with 8.7 ms median on-device latency, 100% session completion, and 0 device-related adverse events. These results demonstrate technical feasibility of embedded, sensor-fused assistance for upper-limb function; formal patient studies under IRB oversight are planned. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_19826 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Neurotremor: A wearable Supportive Device for Supporting Upper Limb Muscle Function Aueawattthanaphisut, Aueaphum Srichaisak, Thanyanee Ieochai, Arissa Neurons and Cognition Emerging Technologies Machine Learning Tissues and Organs A sensor-fused wearable assistance prototype for upper-limb function (triceps brachii and extensor pollicis brevis) is presented. The device integrates surface electromyography (sEMG), an inertial measurement unit (IMU), and flex/force sensors on an M5StickC plus an ESP32-S3 compute hub. Signals are band-pass and notch filtered; features (RMS, MAV, zero-crossings, and 4-12 Hz tremor-band power) are computed in 250 ms windows and fed to an INT8 TensorFlow Lite Micro model. Control commands are bounded by a control-barrier-function safety envelope and delivered within game-based tasks with lightweight personalization. In a pilot technical feasibility evaluation with healthy volunteers (n = 12) performing three ADL-oriented tasks, tremor prominence decreased (Delta TI = -0.092, 95% CI [-0.102, -0.079]), range of motion increased (+12.65%, 95% CI [+8.43, +13.89]), repetitions rose (+2.99 min^-1, 95% CI [+2.61, +3.35]), and the EMG median-frequency slope became less negative (Delta = +0.100 Hz/min, 95% CI [+0.083, +0.127]). The sensing-to-assist loop ran at 100 Hz with 8.7 ms median on-device latency, 100% session completion, and 0 device-related adverse events. These results demonstrate technical feasibility of embedded, sensor-fused assistance for upper-limb function; formal patient studies under IRB oversight are planned. |
| title | Neurotremor: A wearable Supportive Device for Supporting Upper Limb Muscle Function |
| topic | Neurons and Cognition Emerging Technologies Machine Learning Tissues and Organs |
| url | https://arxiv.org/abs/2510.19826 |