Literature DB >> 23110821

Inertial sensor motion analysis of gait, sit-stand transfers and step-up transfers: differentiating knee patients from healthy controls.

S A A N Bolink1, S N van Laarhoven, M Lipperts, I C Heyligers, B Grimm.   

Abstract

Patients undergoing total knee replacement for end stage knee osteoarthritis (OA) become increasingly younger and more demanding. Consequently, outcome assessment tools need to evolve toward objective performance-based measures. We applied a novel approach toward ambulatory biomechanical assessment of physical function using a single inertial sensor located at the pelvis to derive various motion parameters during activities of daily living. We investigated the potential of a clinically feasible battery of tests to define relevant parameters of physical function. We compared preoperative measures of end stage knee OA patients to healthy subjects. Our results show that measures of time yield the highest discriminative capacity to differentiate between groups. Additionally we found disease-dependent and task-specific alterations of movement for inertial sensor-derived motion parameters with good discriminative capacity. The inertial sensor's output quantities seem to capture another clinically relevant dimension of physical function that is supplementary to time. This study demonstrates the potential of inertial sensor-based motion analysis and provides a standardized test feasible for a routine clinical application in the longitudinal follow-up.

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Year:  2012        PMID: 23110821     DOI: 10.1088/0967-3334/33/11/1947

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  13 in total

1.  Measuring clinically relevant knee motion with a self-calibrated wearable sensor.

Authors:  Todd J Hullfish; Feini Qu; Brendan D Stoeckl; Peter M Gebhard; Robert L Mauck; Josh R Baxter
Journal:  J Biomech       Date:  2019-04-05       Impact factor: 2.712

Review 2.  Gait metrics analysis utilizing single-point inertial measurement units: a systematic review.

Authors:  Ralph Jasper Mobbs; Jordan Perring; Suresh Mahendra Raj; Monish Maharaj; Nicole Kah Mun Yoong; Luke Wicent Sy; Rannulu Dineth Fonseka; Pragadesh Natarajan; Wen Jie Choy
Journal:  Mhealth       Date:  2022-01-20

3.  A high rate of tibial plateau fractures after early experience with patient-specific instrumentation for unicompartmental knee arthroplasties.

Authors:  A M Leenders; M G M Schotanus; R J P Wind; R A P Borghans; N P Kort
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2018-04-30       Impact factor: 4.342

4.  Estimation of pelvis kinematics in level walking based on a single inertial sensor positioned close to the sacrum: validation on healthy subjects with stereophotogrammetric system.

Authors:  Francesca Buganè; Maria Grazia Benedetti; Valentina D'Angeli; Alberto Leardini
Journal:  Biomed Eng Online       Date:  2014-10-21       Impact factor: 2.819

5.  Examination of Inertial Sensor-Based Estimation Methods of Lower Limb Joint Moments and Ground Reaction Force: Results for Squat and Sit-to-Stand Movements in the Sagittal Plane.

Authors:  Jun Kodama; Takashi Watanabe
Journal:  Sensors (Basel)       Date:  2016-08-01       Impact factor: 3.576

6.  Evaluating physical function and activity in the elderly patient using wearable motion sensors.

Authors:  Bernd Grimm; Stijn Bolink
Journal:  EFORT Open Rev       Date:  2017-03-13

7.  A Comparison of the Conventional PiG Marker Method Versus a Cluster-Based Model when recording Gait Kinematics in Trans-Tibial Prosthesis Users and the Implications for Future IMU Gait Analysis.

Authors:  Manunchaya Samala; Philip Rowe; Jutima Rattanakoch; Gary Guerra
Journal:  Sensors (Basel)       Date:  2020-02-25       Impact factor: 3.576

8.  Assessment of Sit-to-Stand Transfers during Daily Life Using an Accelerometer on the Lower Back.

Authors:  Lukas Adamowicz; F Isik Karahanoglu; Christopher Cicalo; Hao Zhang; Charmaine Demanuele; Mar Santamaria; Xuemei Cai; Shyamal Patel
Journal:  Sensors (Basel)       Date:  2020-11-19       Impact factor: 3.576

9.  Are patients with knee osteoarthritis and patients with knee joint replacement as physically active as healthy persons?

Authors:  Rikke Daugaard; Marianne Tjur; Maik Sliepen; Matthijs Lipperts; Bernd Grimm; Inger Mechlenburg
Journal:  J Orthop Translat       Date:  2018-04-03       Impact factor: 5.191

10.  Deep Learning in Gait Parameter Prediction for OA and TKA Patients Wearing IMU Sensors.

Authors:  Mohsen Sharifi Renani; Casey A Myers; Rohola Zandie; Mohammad H Mahoor; Bradley S Davidson; Chadd W Clary
Journal:  Sensors (Basel)       Date:  2020-09-28       Impact factor: 3.576

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