Mobile Robot Assisted Gait Monitoring and Dynamic Margin of Stability Estimation

Chen, Zhuo; Zhang, Huanghe; Zaferiou, Antonia M.; Zanotto, Damiano; Guo, Yi

doi:10.1109/tmrb.2022.3162148

Cited by 6 publications

(4 citation statements)

References 42 publications

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“…Stride length (SL) was determined as the distance between two successive IMU locations of the same foot at FF. Stride velocity (SV) was computed as the ratio of SL over ST. A detailed description of this method is presented in Chen et al ( 2022 ).…”

Section: Autonomous Gait Monitoring and Mos Estimationmentioning

confidence: 99%

“…Subsequently, the following three scalars were extracted at each gait cycle: was the mean of the AP projection of the MoS measured over the gait cycle; ( ) was the positive (negative) ML projection of the MoS integrated over the gait cycle. More details on the EFK-based method for MoS estimation can be found in Chen et al ( 2022 ).…”

Section: Autonomous Gait Monitoring and Mos Estimationmentioning

confidence: 99%

“…Survey results that measure participants' attitudes toward technology and our integrated system are reported with summarized data. While our recent work Chen et al, 2022) focused on spatiotemporal gait analysis and MoS estimation, and validated these methods with healthy individuals under controlled laboratory conditions, this article focuses on validation of the system with older adults at a community center in guided walking exercises with a clinically-oriented protocol. New contributions include the following:…”

Section: Introductionmentioning

confidence: 99%

“…While our recent work (Zhang et al, 2020 ; Chen et al, 2022 ) focused on spatiotemporal gait analysis and MoS estimation, and validated these methods with healthy individuals under controlled laboratory conditions, this article focuses on validation of the system with older adults at a community center in guided walking exercises with a clinically-oriented protocol. New contributions include the following: (1) a design of mobile robot motion planning and distance-keeping control to guide older adults in walking exercises; (2) an evaluation of the system’s accuracy on gait monitoring during walking exercises with older adults in a community center; (3) an investigation of how the Montreal Cognitive Assessment (MoCA) score, a clinical measure of cognitive function, is independently associated with changes in gait and balance metrics captured by the integrated system during dual-task walking in older adults; (4) an analysis of older adults’ attitude toward the proposed technology.…”

Section: Introductionmentioning

confidence: 99%

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Gait monitoring for older adults during guided walking: An integrated assistive robot and wearable sensor approach

et al. 2022

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An active lifestyle can mitigate physical decline and cognitive impairment in older adults. Regular walking exercises for older individuals result in enhanced balance and reduced risk of falling. In this article, we present a study on gait monitoring for older adults during walking using an integrated system encompassing an assistive robot and wearable sensors. The system fuses data from the robot onboard Red Green Blue plus Depth (RGB-D) sensor with inertial and pressure sensors embedded in shoe insoles, and estimates spatiotemporal gait parameters and dynamic margin of stability in real-time. Data collected with 24 participants at a community center reveal associations between gait parameters, physical performance (evaluated with the Short Physical Performance Battery), and cognitive ability (measured with the Montreal Cognitive Assessment). The results validate the feasibility of using such a portable system in out-of-the-lab conditions and will be helpful for designing future technology-enhanced exercise interventions to improve balance, mobility, and strength and potentially reduce falls in older adults.

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Section: Autonomous Gait Monitoring and Mos Estimationmentioning

confidence: 99%