ArticleScientific reports2021
Portable, open-source solutions for estimating wrist position during reaching in people with stroke.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Myoelectric interface for neurorehabilitation conditioning to reduce abnormal leg co-activation after stroke: a pilot study.Journal of neuroengineering and rehabilitation · 2024Trial
- Wearable Myoelectric Interface for Neurorehabilitation (MINT) to Recover Arm Activity After Stroke: A Randomized Controlled Trial.Neurorehabilitation and neural repair · 2026Article
- AI-driven low-cost rehabilitation exergame as a lightweight framework for stroke assessment.NPJ digital medicine · 2026Article
- Kinematic instrumental assessment quantifies compensatory strategies in post-stroke patients.Medical & biological engineering & computing · 2026Observational
- A quantitative assessment of the hand kinematic features estimated by the oculus Quest 2.Scientific reports · 2025Article
- The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions.Bioengineering (Basel, Switzerland) · 2024Review
- Myoelectric interface for neurorehabilitation conditioning to reduce abnormal leg co-activation after stroke: a pilot study.Research square · 2023Article
- Computer-assisted approaches for measuring, segmenting, and analyzing functional upper extremity movement: a narrative review of the current state, limitations, and future directions.Frontiers in rehabilitation sciences · 2023Review
- Assessing the validity of inertial measurement units for shoulder kinematics using a commercial sensor-software system: A validation study.Health science reports · 2022Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Arm movement kinematics may provide a more sensitive way to assess neurorehabilitation outcomes than existing metrics. However, measuring arm kinematics in people with stroke can be challenging for traditional optical tracking systems due to non-ideal environments, expense, and difficulty performing required calibration. Here, we present two open-source methods, one using inertial measurement units (IMUs) and another using virtual reality (Vive) sensors, for accurate measurements of wrist position with respect to the shoulder during reaching movements in people with stroke. We assessed the accuracy of each method during a 3D reaching task. We also demonstrated each method's ability to track two metrics derived from kinematics-sweep area and smoothness-in people with chronic stroke. We computed correlation coefficients between the kinematics estimated by each method when appropriate. Compared to a traditional optical tracking system, both methods accurately tracked the wrist during reaching, with mean signed errors of 0.09 ± 1.81 cm and 0.48 ± 1.58 cm for the IMUs and Vive, respectively. Furthermore, both methods' estimated kinematics were highly correlated with each other (p < 0.01). By using relatively inexpensive wearable sensors, these methods may be useful for developing kinematic metrics to evaluate stroke rehabilitation outcomes in both laboratory and clinical environments.
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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.