ArticleSoft robotics2022
Smart Skin: Vision-Based Soft Pressure Sensing System for In-Home Hand Rehabilitation.
Article in Soft robotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- From imaging enhancement to surgical autonomy: the evolutionary role of nanotechnology in AI-driven robotic surgery.Discover nano · 2026Review
- Smart Clothing and Medical Imaging Innovations for Real-Time Monitoring and Early Detection of Stroke: Bridging Technology and Patient Care.Diagnostics (Basel, Switzerland) · 2025Review
- From Sensors to Care: How Robotic Skin Is Transforming Modern Healthcare-A Mini Review.Sensors (Basel, Switzerland) · 2025Review
- AI Applications in Adult Stroke Recovery and Rehabilitation: A Scoping Review Using AI.Sensors (Basel, Switzerland) · 2024Article
- Wearable rehabilitation wristband for distal radius fractures.Frontiers in neuroscience · 2023Article
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Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce a novel in-home hand rehabilitation system for monitoring hand motions and assessing grip forces of stroke patients. The overall system is composed of a sensing device and a computer vision system. The sensing device is a lightweight cylindrical object for easy grip and manipulation, which is covered by a passive sensing layer called "Smart Skin." The Smart Skin is fabricated using soft silicone elastomer, which contains embedded microchannels partially filled with colored fluid. When the Smart Skin is compressed by grip forces, the colored fluid rises and fills in the top surface display area. Then, the computer vision system captures the image of the display area through a red-green-blue camera, detects the length change of the liquid through image processing, and eventually maps the liquid length to the calibrated force for estimating the gripping force. The passive sensing mechanism of the proposed Smart Skin device works in conjunction with a single camera setup, making the system simple and easy to use, while also requiring minimum maintenance effort. Our system, on one hand, aims to support home-based rehabilitation therapy with minimal or no supervision by recording the training process and the force data, which can be automatically conveyed to physical therapists. In contrast, the therapists can also remotely instruct the patients with their training prescriptions through online videos. This study first describes the design, fabrication, and calibration of the Smart Skin, and the algorithm for image processing, and then presents experimental results from the integrated system. The Smart Skin prototype shows a relatively linear relationship between the applied force and the length change of the liquid in the range of 0-35 N. The computer vision system shows the estimation error <4% and a relatively high stability in estimation under different hand motions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.