A Wearable Resistance Devices Motor Learning Effects in Exercise
<|reference_start|>A Wearable Resistance Devices Motor Learning Effects in Exercise: The integration of technology into exercise regimens has emerged as a strategy to enhance normal human capabilities and return human motor function after injury or illness by enhancing motor learning and retention. Much research has focused on how active devices, whether confined to a lab or made into a wearable format, can apply forces at set times and conditions to optimize the process of learning. However, the focus on active force production often forces devices to either be confined to simple movements or interventions. As such, in this paper, we investigate how passive device behaviors can contribute to the process of motor learning by themselves. Our approach involves using a wearable resistance (WR) device, which is outfitted with elastic bands, to apply a force field that changes in response to a person's movements while performing exercises. We develop a method to measure the produced forces from the device without impeding the function and we characterize the device's force generation abilities. We then present a study assessing the impact of the WR device on motor learning of proper squat form compared to visual or no feedback. Biometrics such as knee and hip angles were used to monitor and assess subject performance. Our findings indicate that the force fields produced while training with the WR device can improve performance in full-body exercises similarly to a more direct visual feedback mechanism, though the improvement is not consistent across all performance metrics. Through our research, we contribute important insights into the application of passive wearable resistance technology in practical exercise settings.<|reference_end|>
@article{frias-miranda2024a,
    title={A Wearable Resistance Devices Motor Learning Effects in Exercise},
    author={Eugenio Frias-Miranda, Hong-Anh Nguyen, Jeremy Hampton, Trenner Jones,
  Benjamin Spotts, Matthew Cochran, Deva Chan, Laura H Blumenschein},
    journal={arXiv preprint arXiv:2405.15113},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.15113},
    primaryClass={cs.RO}
}