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Assistive strategies for occupational back-support exoskeletons have focused, mostly, on lifting tasks. However, in occupational scenarios, it is important to account not only for lifting but also for other activities. This can be done exploiting human activity recognition algorithms that can identify which task the user is performing and trigger the appropriate assistive strategy. We refer to this ability as exoskeleton versatility. To evaluate versatility, we propose to focus both on the ability of the device to reduce muscle activation (efficacy) and on its interaction with the user (dynamic fit). To this end, we performed an experimental study involving healthy subjects replicating the working activities of a manufacturing plant. To compare versatile and non-versatile exoskeletons, our device, XoTrunk, was controlled with two different strategies. Correspondingly, we collected muscle activity, kinematic variables and users' subjective feedbacks. Also, we evaluated the task recognition performance of the device. The results show that XoTrunk is capable of reducing muscle activation by up to in lifting and in carrying. However, the non-versatile control strategy hindered the users' natural gait (e.g., reduction of hip flexion), which could potentially lower the exoskeleton acceptance. Detecting carrying activities and adapting the control strategy, resulted in a more natural gait (e.g., increase of hip flexion). The classifier analyzed in this work, showed promising performance (online accuracy > 91%). Finally, we conducted 9 hours of field testing, involving four users. Initial subjective feedbacks on the exoskeleton versatility, are presented at the end of this work.
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http://dx.doi.org/10.1017/wtc.2021.9 | DOI Listing |
Wearable Technol
September 2021
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy.
Assistive strategies for occupational back-support exoskeletons have focused, mostly, on lifting tasks. However, in occupational scenarios, it is important to account not only for lifting but also for other activities. This can be done exploiting human activity recognition algorithms that can identify which task the user is performing and trigger the appropriate assistive strategy.
View Article and Find Full Text PDFSex Abuse
January 2003
School of Criminology and Criminal Justice, School of Applied Psychology, Mt Gravatt Campus, Griffith University, Queensland 4111, Australia.
Associations between trait empathy and criminal versatility were examined in a sample of 88 incarcerated adult sexual offenders (29 extrafamilial child molesters, 26 intrafamilial child molesters, and 33 rapists). Considerable criminal versatility was observed, with 60% of the whole sample and 88% of recidivist offenders having previous convictions for nonsexual offenses. Regression analyses showed significant associations between trait empathy and nonsexual offense convictions, but not between trait empathy and sexual offense convictions.
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