A Smart Shoe Insole to Monitor Frail Older Adults’ Walking Speed: Results of Two Evaluation Phases Completed in a Living Lab and Through a 12-Week Pilot Study
Notice bibliographique
Résumé
BACKGROUND: Recent World Health Organization reports propose wearable devices to collect information on activity and walking speed as innovative health indicators. However, mainstream consumer-grade tracking devices and smartphone apps are often inaccurate and require long-term acceptability assessment. OBJECTIVE: Our aim is to assess the user acceptability of an instrumented shoe insole in frail older adults. This device monitors participants' walking speed and differentiates active walking from shuffling after step length calibration. METHODS: A multiphase evaluation has been designed: 9 older adults were evaluated in a living lab for a day, 3 older adults were evaluated at home for a month, and a prospective randomized trial included 35 older adults at home for 3 months. A qualitative research design using face-to-face and phone semistructured interviews was performed. Our hypothesis was that this shoe insole was acceptable in monitoring long-term outdoor and indoor walking. The primary outcome was participants' acceptability, measured by a qualitative questionnaire and average time of insole wearing per day. The secondary outcome described physical frailty evolution in both groups. RESULTS: Living lab results confirmed the importance of a multiphase design study with participant involvement. Participants proposed insole modifications. Overall acceptability had mixed results: low scores for reliability (2.1 out of 6) and high scores for usability (4.3 out of 6) outcomes. The calibration phase raised no particular concern. During the field test, a majority of participants (mean age 79 years) were very (10/16) or quite satisfied (3/16) with the insole's comfort at the end of the follow-up. Participant insole acceptability evolved as follows: 63% (12/19) at 1 month, 50% (9/18) at 2 months, and 75% (12/16) at 3 months. A total of 9 participants in the intervention group discontinued the intervention because of technical issues. All participants equipped for more than a week reported wearing the insole every day at 1 month, 83% (15/18) at 2 months, and 94% (15/16) at 3 months for 5.8, 6.3, and 5.1 hours per day, respectively. Insole data confirmed that participants effectively wore the insole without significant decline during follow-up for an average of 13.5 days per 4 months and 5.6 hours per day. For secondary end points, the change in frailty parameters or quality of life did not differ for those randomly assigned to the intervention group compared to usual care. CONCLUSIONS: Our study reports acceptability data on an instrumented insole in indoor and outdoor walking with remote monitoring in frail older adults under real-life conditions. To date, there is limited data in this population set. This thin instrumentation, including a flexible battery, was a technical challenge and seems to provide an acceptable solution over time that is valued by participants. However, users still raised certain acceptability issues. Given the growing interest in wearable health care devices, these results will be useful for future developments. TRIAL REGISTRATION: ClinicalTrials.gov NCT02316600; https://clinicaltrials.gov/ct2/show/NCT02316600.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».