ArticleSensors (Basel, Switzerland)2025
A Wearable System for Knee Osteoarthritis: Based on Multimodal Physiological Signal Assessment and Intelligent Rehabilitation.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- A Real-Time Digital Twin Synchronization Framework for Multi-Sensor Cardiopulmonary Resuscitation Measurement.Sensors (Basel, Switzerland) · 2026Article
- Agreement Between Video-Based and In-Person Assessment in Patients with Knee Pain-A Prospective Repeated-Measures Pragmatic Study.Journal of clinical medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Knee osteoarthritis (KOA), a common degenerative joint disease, affects a large patient population and poses significant challenges in early diagnosis and rehabilitation. Achieving precise assessment of knee function and efficient home-based intelligent rehabilitation is crucial for alleviating pain, slowing disease progression, and improving patients' quality of life. This study proposes a smart wearable knee function assessment based on multimodal physiological signals and a rehabilitation system. The system integrates surface electromyography (sEMG), pressure sensors, and an inertial measurement unit (IMU) to synchronously capture gait, posture, and muscle activity. It quantifies knee function by extracting gait and EMG features. Additionally, a wearable massage device driven by airbags was designed and implemented to simulate the traditional Chinese medicine "seated knee-adjustment method" and deliver precise intelligent rehabilitation interventions. Experimental results validated the system's accuracy in functional assessment and reliability in rehabilitation assistance. The average relative error in gait feature extraction was below 8%, while the massage head displacement error remained within clinically acceptable ranges. By integrating multimodal sensing technology with intelligent rehabilitation devices, this system offers KOA patients a convenient, efficient, and sustainable home-based rehabilitation solution with strong clinical application potential and promotional value.
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What Socratic holds
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 Socratic graph.