Exoskeletons in the Digital Era: A Way to Improve the Level of Physical Activity Among Older Citizens
Bibliographic record
Abstract
Background The COVID-19 pandemic has had a negative impact on the level of physical activity among older citizens. Objective The aim of this short paper is to set focus on the potential benefits of assistive walking devices for older citizens. Methods In this feasibility study, 24 older citizens aged >65 years participated in the study. The participants answered to the following questionnaires after fulfilling a consent form: Tilburg Frailty Indicator, International Physical Activity Questionnaire, and Quality of Life. Then, physiological and biomechanical assessments were made in a laboratory setting with and without wearing an exoskeleton (aLQ, IMASEN Electrical Industrial Co). The aLQ is a passive-assistive lower-limb walking exoskeleton activated by a cam spring system designed to improve gait. After the tests, the participants were asked to answer the following questions: “Do you feel the exoskeleton is helping you to walk?” and “What is your opinion on the device?”. Results The participants were community-dwelling older individuals, aged 72.6 (SD 4.5) years, and were characterized by an overall high level of physical activity of 3069 (SD 2847) metabolic equivalent–minutes per week. Their Tilburg Frailty Indicator indicated an overall frailty score of 3.5 (SD 2.5). The participants reported a Quality of Life score of 6.7 (SD 1.6) and an overall health score of 76.4 (SD 17.1). Moreover, of the 24 participants, 7 (29%) reported that carrying the tested exoskeleton did not induce any noticeable changes, and 3 (10%) reported that they walked better with the device than without. Conclusions These findings are of importance in our current digital era where the COVID-19 pandemic forced municipalities and hospitals to cancel or postpone the training and rehabilitation of older citizens, resulting in a degradation of the level of physical activity and health in general. The use of assistive walking devices can be a way to improve or maintain their level of physical activity. Future studies using a prospective design should confirm that. Conflicts of Interest None declared.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".