Literature DB >> 28269456

Skin mounted accelerometer system for measuring knee range of motion.

Ryan S McGinnis, Shyamal Patel, Ikaro Silva, Nikhil Mahadevan, Steve DiCristofaro, Elise Jortberg, Melissa Ceruolo, A J Aranyosi.   

Abstract

Sufficient range of motion of the knee joint is necessary for performing many activities of daily living. Ambulatory monitoring of knee function can provide valuable information about progression of diseases like knee osteoarthritis and recovery after surgical interventions like total knee arthroplasty. In this paper, we describe a skin-mounted, conformal, accelerometer-based system for measuring knee angle and range of motion that does not require a skilled operator to apply devices. We establish the accuracy of this technique with respect to clinical gold standard goniometric measurements on a dataset collected from normative subjects during the performance of repeated bouts of knee flexion and extension tests. Results show that knee angle and range of motion estimates are highly correlated with goniometer measurements, and track differences in knee angle and range of motion to within 1%. These results demonstrate the ability of this system to characterize knee angle and range of motion, enabling future longitudinal monitoring of knee motion in naturalistic environments.

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Year:  2016        PMID: 28269456     DOI: 10.1109/EMBC.2016.7591923

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  9 in total

Review 1.  Next Steps in Wearable Technology and Community Ambulation in Multiple Sclerosis.

Authors:  Mikaela L Frechette; Brett M Meyer; Lindsey J Tulipani; Reed D Gurchiek; Ryan S McGinnis; Jacob J Sosnoff
Journal:  Curr Neurol Neurosci Rep       Date:  2019-09-04       Impact factor: 5.081

2.  Metrics extracted from a single wearable sensor during sit-stand transitions relate to mobility impairment and fall risk in people with multiple sclerosis.

Authors:  Lindsey J Tulipani; Brett Meyer; Dale Larie; Andrew J Solomon; Ryan S McGinnis
Journal:  Gait Posture       Date:  2020-06-20       Impact factor: 2.840

3.  Evaluating the use of machine learning in the assessment of joint angle using a single inertial sensor.

Authors:  Rob Argent; Sean Drummond; Alexandria Remus; Martin O'Reilly; Brian Caulfield
Journal:  J Rehabil Assist Technol Eng       Date:  2019-08-19

4.  Validation of Novel Relative Orientation and Inertial Sensor-to-Segment Alignment Algorithms for Estimating 3D Hip Joint Angles.

Authors:  Lukas Adamowicz; Reed D Gurchiek; Jonathan Ferri; Anna T Ursiny; Niccolo Fiorentino; Ryan S McGinnis
Journal:  Sensors (Basel)       Date:  2019-11-24       Impact factor: 3.576

5.  A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement.

Authors:  Nan Lou; Yanan Diao; Qiangqiang Chen; Yunkun Ning; Gaoqiang Li; Shengyun Liang; Guanglin Li; Guoru Zhao
Journal:  Front Neurorobot       Date:  2022-03-23       Impact factor: 2.650

6.  Efficacy of interspace between the popliteal artery and the capsule of the posterior knee (iPACK) block versus periarticular local infiltration analgesia after unilateral total knee arthroplasty: Prospective randomized control trial.

Authors:  Abdul Sattar Narejo; Fatima Abdulwahab; Mansoor Aqil; Abdullah T Alsubaie; Hassan Y Hazazy; Tariq Alzahrani; Abdulaziz Aljurayyan; Ahmed Thallaj
Journal:  Saudi Med J       Date:  2021-10       Impact factor: 1.422

7.  A Pivotal Study to Validate the Performance of a Novel Wearable Sensor and System for Biometric Monitoring in Clinical and Remote Environments.

Authors:  Ellora Sen-Gupta; Donald E Wright; James W Caccese; John A Wright; Elise Jortberg; Viprali Bhatkar; Melissa Ceruolo; Roozbeh Ghaffari; Dennis L Clason; James P Maynard; Arthur H Combs
Journal:  Digit Biomark       Date:  2019-03-01

8.  Soft Smart Garments for Lower Limb Joint Position Analysis.

Authors:  Massimo Totaro; Tommaso Poliero; Alessio Mondini; Chiara Lucarotti; Giovanni Cairoli; Jesùs Ortiz; Lucia Beccai
Journal:  Sensors (Basel)       Date:  2017-10-12       Impact factor: 3.576

Review 9.  Estimating Biomechanical Time-Series with Wearable Sensors: A Systematic Review of Machine Learning Techniques.

Authors:  Reed D Gurchiek; Nick Cheney; Ryan S McGinnis
Journal:  Sensors (Basel)       Date:  2019-11-28       Impact factor: 3.576

  9 in total

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