ArticleSensors (Basel, Switzerland)2017
Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03651739 (Knee Connect), which is not on this map. Cited by 46 papers, 2 of them syntheses that pooled it.
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.
Knee Connect: Measuring Range of Motion and Gait Metrics After Total Knee Arthroplasty
Who cites it
46 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.
- Readiness for implementation of novel digital health interventions for postoperative monitoring: a systematic review and clinical innovation network analysis.The Lancet. Digital health · 2023Pooled it
- A Systematic Review of Diagnostic Accuracy and Clinical Applications of Wearable Movement Sensors for Knee Joint Rehabilitation.Sensors (Basel, Switzerland) · 2021Pooled it
- Clinical application research of intelligent monitoring system for knee rehabilitation: a randomized controlled trial.Journal of orthopaedic surgery and research · 2024Trial
- Movement smoothness and plasma proteomics are associated with functional impairment in knee osteoarthritis.Osteoarthritis and cartilage open · 2026Article
- From One-Size-Fits-All to Data-Driven Recovery: A Narrative Review of Wearable Technologies Toward Personalized Rehabilitation After Total Hip and Knee Arthroplasty.Journal of personalized medicine · 2026Review
- Digital range of motion analysis is sensitive to subjective steps in joint model construction.Journal of anatomy · 2026Article
- Use and Application of mHealth Technologies in Perioperative Surgical Care: Narrative Review.JMIR mHealth and uHealth · 2025Review
- Proteomic analysis reveals biomarkers associated with performance-based joint function and patient-reported outcomes in knee osteoarthritis.Osteoarthritis and cartilage open · 2025Article
- Effect of low-intensity muscle strength training on postoperative rehabilitation and adverse events in patients with knee osteoarthritis over 55 years of age: a meta-analysis.BMC sports science, medicine & rehabilitation · 2024Article
- [Postoperative rehabilitation after knee arthroplasty].Orthopadie (Heidelberg, Germany) · 2024Review
- [The potential of wearable technology in knee arthroplasty].Orthopadie (Heidelberg, Germany) · 2024Review
- Inertial Measurement Unit-Based Frozen Shoulder Identification from Daily Shoulder Tasks Using Machine Learning Approaches.Sensors (Basel, Switzerland) · 2024Article
- The Intrarater and Interrater Reliability and Validity of Universal Goniometer, Digital Inclinometer, and Smartphone Application Measuring Range of Motion in Patients with Total Knee Arthroplasty.Indian journal of orthopaedics · 2024Article
- Mobile and Computer-Based Applications for Rehabilitation Monitoring and Self-Management After Knee Arthroplasty: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Postoperative Activity and Knee Function of Patients after Total Knee Arthroplasty: A Sensor-Based Monitoring Study.Journal of personalized medicine · 2023Article
- Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review.Sensors (Basel, Switzerland) · 2023Review
- The Role of Wearable Technology in Measuring and Supporting Patient Outcomes Following Total Joint Replacement: Review of the Literature.JMIR perioperative medicine · 2023Review
- A Framework for Analytical Validation of Inertial-Sensor-Based Knee Kinematics Using a Six-Degrees-of-Freedom Joint Simulator.Sensors (Basel, Switzerland) · 2022Article
- Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review.JMIR rehabilitation and assistive technologies · 2022Review
- Artificial intelligence in knee arthroplasty: current concept of the available clinical applications.Arthroplasty (London, England) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Total knee arthroplasty (TKA) is the most common treatment for degenerative osteoarthritis of that articulation. However, either in rehabilitation clinics or in hospital wards, the knee range of motion (ROM) can currently only be assessed using a goniometer. In order to provide continuous and objective measurements of knee ROM, we propose the use of wearable inertial sensors to record the knee ROM during the recovery progress. Digitalized and objective data can assist the surgeons to control the recovery status and flexibly adjust rehabilitation programs during the early acute inpatient stage. The more knee flexion ROM regained during the early inpatient period, the better the long-term knee recovery will be and the sooner early discharge can be achieved. The results of this work show that the proposed wearable sensor approach can provide an alternative for continuous monitoring and objective assessment of knee ROM recovery progress for TKA patients compared to the traditional goniometer measurements.
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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.