Bio-Inspired Self-Supervised Learning for Wrist-worn IMU Signals | ScienceToStartup | ScienceToStartup

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References (35)

[1]

LSM-2: Learning from Incomplete Wearable Sensor Data

2025Maxwell A. Xu, Girish Narayanswamy et al.

[2]

Wearable-based digital biomarker provides a valid alternative to traditional clinical measures for post-stroke upper-limb motor recovery

2025Ryan Wang, C. E. Lang et al.

[3]

Past, Present, and Future of Sensor-based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task

Founder's Pitch

"A novel self-supervised learning approach for robust human activity recognition using wrist-worn IMU signals."

Wearable Health Monitoring•Score: 8•View PDF ↗

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2/4 signals

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7.5

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Bio-Inspired Self-Supervised Learning for Wrist-worn IMU Signals

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References (35)

Founder's Pitch

"A novel self-supervised learning approach for robust human activity recognition using wrist-worn IMU signals."

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Bio-Inspired Self-Supervised Learning for Wrist-worn IMU Signals

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References (35)

Founder's Pitch

"A novel self-supervised learning approach for robust human activity recognition using wrist-worn IMU signals."

Commercial Viability Breakdown

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