Patient Acceptability and Technical Reliability of Wearable Devices Used for Monitoring People With Parkinson Disease: Survey Study
Notice bibliographique
Résumé
Background: Parkinson disease is a progressive neurodegenerative disorder with complex motor and nonmotor symptoms. To assess these, clinical assessments are completed, providing a snapshot of a person's experience. Monitoring Parkinson disease using wearable devices can provide continuous and objective data and capture information on movement patterns in daily life. Objective: The aim of the study is to assess patient acceptability and technical reliability of 2 wearable devices used in clinical trials (ActivInsights and Axivity AX3). Methods: Participants in a feasibility study testing a self-management toolkit (PD-Care) optionally wore a wearable device for 1 week, providing feedback through an open- and closed-question survey conducted over the telephone about the acceptability of wearing the device. The closed questions used a Likert scale from 1 to 5 (with 1=strongly agree and 5=strongly disagree) asking whether (1) the device was comfortable to wear, (2) the device was easy to put on, (3) the device was easy to wear, (4) the device was embarrassing to wear, and (5) if they were happy to wear the device for longer than 7 days. Differences in acceptability between devices were analyzed using Mann-Whitney U tests and Wilcoxon matched pairs signed rank tests. These were followed by open-ended questions asking (1) How did you find wearing the device? (2) How did you find putting the device on? (3) Did you take it off and why? (4) What was your overall impression? (5) Did you prefer the wrist- or trunk-worn device and why (Axivity AX3 only)? Results: A total of 22 of 32 (69%) participants offered the device agreed to wear it. There were no significant differences in the demographic characteristics between those monitored and those who chose not to be. Acceptance with both devices was generally good. The ActivInsights device was more acceptable than the wrist- and trunk-worn Axivity AX3 devices, as more participants found it to be comfortable (n=15, 100% vs n=5, 71%; P=.02 and n=4, 57%; P=.004, respectively), easy to wear (n=15, 100% vs n=6, 86%; P=.048 and n=3, 43%; P=.004, respectively) and would wear for more than 7 days (n=13, 87% vs n=4, 57%; P=.02 and n=1, 14%; P<.001, respectively). The trunk-worn Axivity AX3 device had the lowest acceptance rates, but there were no statistical differences in acceptability between the wrist- and trunk-worn Axivity AX3 devices (all P>.05). There were issues with battery life and recording errors in 3 of 14 (21%) Axivity AX3 devices and upload failures in 3 of 15 (20%) ActivInsights devices. Conclusions: Acceptability of wearables for monitoring Parkinson was satisfactory, especially when wrist-worn, although a few participants experienced difficulties in correct use, and there were some errors with the data upload.
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 | 0,012 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 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 ».