Development of a wearable multi-sensor system for lower limb joint torque evaluation during stairs climbing

Wu, Qingcong; Wang, Xingsong; Zhang, Xiaobo; Chen, Bai; Shao, Ziyan; Lu, Longhai

doi:10.1109/rcar.2017.8311875

Cited by 2 publications

(2 citation statements)

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“…Among them, two studies additionally performed running turns [ 57 , 60 ]. Other activities analyzed included lifting and carrying loads [ 61 , 62 , 63 , 64 , 65 , 66 , 67 ], sit-to-stand [ 55 , 58 , 68 , 69 , 70 , 71 ], stair ascent and descent [ 55 , 58 , 70 , 72 ], standing [ 58 , 73 , 74 ], and trunk bending [ 75 ]. In addition, four studies conducted a kinetic analysis of winter sports, including snowboarding [ 76 ], ski jumping, [ 77 ], skiing [ 78 ], and skating [ 79 ].…”

Section: Resultsmentioning

confidence: 99%

“…However, a PS cannot measure the horizontal component of the GRF (i.e., shear force) because it obtains the GRF from the one-dimensional pressure data. Accordingly, whereas two studies considered only the vertical component of the GRF in the inverse dynamics [ 64 , 72 ], five studies extended the pressure data to 3D GRF. Rouhani et al [ 34 , 38 ] used a method based on the relationship between the plantar pressure distribution and the GRF components developed in a previous study [ 81 ].…”

Section: Resultsmentioning

confidence: 99%

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Inertial Motion Capture-Based Wearable Systems for Estimation of Joint Kinetics: A Systematic Review

Lee

2022

Sensors

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In biomechanics, joint kinetics has an important role in evaluating the mechanical load of the joint and understanding its motor function. Although an optical motion capture (OMC) system has mainly been used to evaluate joint kinetics in combination with force plates, inertial motion capture (IMC) systems have recently been emerging in joint kinetic analysis due to their wearability and ubiquitous measurement capability. In this regard, numerous studies have been conducted to estimate joint kinetics using IMC-based wearable systems. However, these have not been comprehensively addressed yet. Thus, the aim of this review is to explore the methodology of the current studies on estimating joint kinetic variables by means of an IMC system. From a systematic search of the literature, 48 studies were selected. This paper summarizes the content of the selected literature in terms of the (i) study characteristics, (ii) methodologies, and (iii) study results. The estimation methods of the selected studies are categorized into two types: the inverse dynamics-based method and the machine learning-based method. While these two methods presented different characteristics in estimating the kinetic variables, it was demonstrated in the literature that both methods could be applied with good performance for the kinetic analysis of joints in different daily activities.

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