Is Remote Active Feedback Gait Retraining Comparable to in-Person Retraining 2 Years Post Anterior Cruciate Ligament Reconstruction?

He, J.; Mahtani, Gordhan B.; Chu, Constance R.

doi:10.1016/j.joca.2022.02.193

Cited by 2 publications

(2 citation statements)

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“…However, compared to well tested and compactly designed commercial sensors (Moticon, Germany; Nansense, the United States; Pedar, Germany; Rokoko, Denmark; Tekscan, the United States), in-lab developed systems are mostly manually manufactured, which are far from being widely available to other research groups and individuals. As a result, more and more biomechanical and clinical studies have employed the commonly available commercial sensors to achieve their goal of measurement and assessment (Cutti et al, 2008; van den Noort et al, 2009; Pau et al, 2014; Wannop et al, 2020; Wouda et al, 2021; Fereydounnia et al, 2022; He et al, 2022; Trkov et al, 2022). These studies nevertheless largely focus on one type of sensors, in isolation, which can only provide indications on how good they are in measuring a sub-set of the human movement data and as a result cannot support the internal biomechanical states estimation (Ferrari et al, 2010; Zhang et al, 2013; Braun et al, 2015; Stöggl and Martine, 2016; Oerbekke et al, 2017; Al-Amri et al, 2018; Price, 2018).…”

Section: Introductionmentioning

confidence: 99%

A wearable real-time kinetic measurement sensor setup for human locomotion

Wang

Basu²,

Durandau³

et al. 2023

Wearable Technol.

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Current laboratory-based setups (optical marker cameras + force plates) for human motion measurement require participants to stay in a constrained capture region which forbids rich movement types. This study established a fully wearable system, based on commercially available sensors (inertial measurement units + pressure insoles), that can measure both kinematic and kinetic motion data simultaneously and support wireless frame-by-frame streaming. In addition, its capability and accuracy were tested against a conventional laboratory-based setup. An experiment was conducted, with 9 participants wearing the wearable measurement system and performing 13 daily motion activities, from slow walking to fast running, together with vertical jump, squat, lunge, and single-leg landing, inside the capture space of the laboratory-based motion capture system. The recorded sensor data were post-processed to obtain joint angles, ground reaction forces (GRFs), and joint torques (via multi-body inverse dynamics). Compared to the laboratory-based system, the established wearable measurement system can measure accurate information of all lower limb joint angles (Pearson’s r = 0.929), vertical GRFs (Pearson’s r = 0.954), and ankle joint torques (Pearson’s r = 0.917). Center of pressure (CoP) in the anterior–posterior direction and knee joint torques were fairly matched (Pearson’s r = 0.683 and 0.612, respectively). Calculated hip joint torques and measured medial–lateral CoP did not match with the laboratory-based system (Pearson’s r = 0.21 and 0.47, respectively). Furthermore, both raw and processed datasets are openly accessible (https://doi.org/10.5281/zenodo.6457662). Documentation, data processing codes, and guidelines to establish the real-time wearable kinetic measurement system are also shared (https://github.com/HuaweiWang/WearableMeasurementSystem).

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Section: Introductionmentioning

confidence: 99%

A wearable real-time kinetic measurement sensor setup for human locomotion

Wang

Basu²,

Durandau³

et al. 2023

Wearable Technol.

View full text Add to dashboard Cite

show abstract

“…The studies mentioned above provided verbal instructions or feedback to the users; while that may be effective for in-person clinical sessions, biofeedback systems, which provide auditory, visual, or tactile stimuli, can enable intervention or training in home-based settings [19]. Among these 3 modes, auditory feedback in the form of rhythmic auditory stimulation (RAS) [20], where the user should move in sync with sound cues (generated by a metronome in the simplest case) or music, is the most common form.…”

Section: Introductionmentioning

confidence: 99%

Modulation of Arm Swing Frequency and Gait Using Rhythmic Tactile Feedback

Noghani

Hossain

Hejrati

2022

Preprint

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Due to the neural coupling between upper and lower limbs and the importance of interlimb coordination in human gait, it has been recommended that focusing on appropriate arm swing should be a part of gait rehabilitation in individuals with walking impairments. Despite its vital importance, there is a lack of effective methods to exploit the potential of arm swing inclusion for gait rehabilitation. In this work, we present a lightweight and wireless haptic feedback system that provides highly synchronized vibrotactile cues to the arms to manipulate arm swing and investigate the effects of this manipulation on the subjects' gait in a study with 12 participants (20-44 years). We found the developed system effectively adjusted the subjects' arm swing and stride cycle times by significantly reducing and increasing those parameters by up to 20% and 35%, respectively, compared to their baseline values during normal walking with no feedback. Particularly, the reduction of arms' and legs' cycle times translated into a substantial increase of about 19.3% (on average) in walking speed. The response of the subjects to the feedback was also quantified in both transient and steady-state walking. The analysis of settling times from the transient responses revealed a fast and similar adaptation of both arms' and legs' movements to the feedback for reducing cycle time (i.e., increasing speed). Conversely, larger settling times and the time differences between arms' and legs' responses were observed due to feedback for increasing cycle times (i.e., reducing speed). The results clearly demonstrate the potential of the developed system to induce different arm-swing patterns as well as the ability of the proposed method to modulate key gait parameters through capitalizing on the interlimb neural coupling with implications for gait training.

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Is Remote Active Feedback Gait Retraining Comparable to in-Person Retraining 2 Years Post Anterior Cruciate Ligament Reconstruction?

Cited by 2 publications

References 0 publications

A wearable real-time kinetic measurement sensor setup for human locomotion

A wearable real-time kinetic measurement sensor setup for human locomotion

Modulation of Arm Swing Frequency and Gait Using Rhythmic Tactile Feedback

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