Efficient Self-Attention Model for Speech Recognition-Based Assistive Robots Control

Assistive robots are tools that people living with upper body disabilities can leverage to autonomously perform Activities of Daily Living (ADL). Unfortunately, conventional control methods still rely on low-dimensional, easy-to-implement interfaces such as joysticks that tend to be unintuitive and cumbersome to use. In contrast, vocal commands may represent a viable and intuitive alternative. This work represents an important step toward providing a viable vocal interface for people living with upper limb disabilities by proposing a novel lightweight vocal command recognition system. The proposed model leverages the MobileNet2 architecture, augmenting it with a novel approach to the self-attention mechanism, achieving a new state-of-the-art performance for Keyword Spotting (KWS) on the Google Speech Commands Dataset (GSCD). Moreover, this work presents a new dataset, referred to as the French Speech Commands Dataset (FSCD), comprising 4963 vocal command utterances. Using the GSCD as the source, we used Transfer Learning (TL) to adapt the model to this cross-language task. TL has been shown to significantly improve the model performance on the FSCD. The viability of the proposed approach is further demonstrated through real-life control of a robotic arm by four healthy participants using both the proposed vocal interface and a joystick.

Subjective and objective burden and psychological distress in care partners of older adults with traumatic brain injury

PURPOSE/OBJECTIVE

In care partners of older persons (65 years and older) having sustained traumatic brain injury (TBI), the objectives were (a) to describe subjective burden (emotional, social, financial, and physical burden), objective burden (new roles and responsibilities), and psychological distress at 4 months postinjury, and (b) to explore the predictors of subjective burden and psychological distress.

RESEARCH METHOD/DESIGN

This is an observational study of care partners of older adults with TBI (n = 46; M_age = 65.2 years, SD = 11.2, 87% female). Participants completed the Zarit Burden Interview, the Hospital Anxiety and Depression Scale, the Brain Injury Complaint Questionnaire (measuring difficulties of the injured older adult perceived by the care partner), and the modified Medical Outcomes Study Social Support Survey.

RESULTS

A majority of care partners (88%) reported at least one form of objective burden (e.g., increased/decreased time spent in certain activities post-TBI), 29% perceived at least mild subjective burden, and 27% reported either significant anxiety or depressive symptoms. Linear regressions indicated that a higher number of difficulties reported regarding the injured person and poorer perceived social support predicted higher subjective burden and psychological distress. A younger age of the care partner also predicted a higher subjective burden.

CONCLUSIONS/IMPLICATIONS

This study provides a better understanding of the potential impacts of TBI in older age for care partners. Future research should examine how to support adequately care partners in their psychological adaptation after TBI in an elderly person. (PsycInfo Database Record (c) 2023 APA, all rights reserved).