Advances in Applying Somatosensory Interaction Technology in Geriatric Health Management: Bibliometric Analysis (Preprint)
Notice bibliographique
Résumé
<sec> <title>BACKGROUND</title> Background: Geriatric health management is rapidly developing as the number of older people living with diseases is increasing globally. The current main health management problems of elderly people include the lack of timely information feedback and standardized information collection and continuous monitoring, which make it difficult to establish timely tracking and retrieval of health data. Somatosensory interaction technology (SIT) enables more direct communication and interaction between the device and the surrounding environment, meaning that it can play a role in the field of geriatric health management. </sec> <sec> <title>OBJECTIVE</title> Objective: The purpose of this study was to summarize the current applications of SIT in geriatric health management, analyze the present and future research hotspots, and provide references for researchers in this field. </sec> <sec> <title>METHODS</title> Methods: We searched the Web of Science Core Collection database for literature on “somatosensory interaction technology” and “geriatric health management.” VOSviewer 1.6.18 and CiteSpace 6.1.R6 software were used to perform the bibliometric visualization and clustering, including the number of articles, countries, institutions, authors, references, and keywords. </sec> <sec> <title>RESULTS</title> Results: In total, 1019 documents were included after screening, the number of publications on SIT in geriatric health management is gradually increasing, and the growth rate is accelerating. The top three countries in terms of the number of publications were the United States (n=275), Canada (n=90), and Australia (n=72). The top three institutions in terms of the number of publications were the University of California in the US (n=30), Tel Aviv University in Israel (n=28), and the University of Toronto in Canada (n=24). The top three most prolific authors were Jeffrey, Hausdorff in Israel (n=13), Jaarsma, Tiny (n=12) and Stromberg, Anna (n=12) in Sweden. A few high-level comprehensive universities and prolific authors lead most of the research. Their collaborations are characterized by a concentration in the same country but global fragmentation. Keyword clustering revealed that research directions were clustered around “risk assessment,” “somatic abilities,” “rehabilitation training,” and “mental health promotion.” Research hotspots of recent years included “machine learning,” “games,” and “dementia.” </sec> <sec> <title>CONCLUSIONS</title> Conclusions: Publications in the field have been increasing at an accelerated rate. However, the increase in core publications is mainly concentrated in individual developed countries and individual authors. There must be greater cross-country and cross-population promotion. SIT can be applied in the risk assessment, somatic abilities, rehabilitation training, and mental health promotion of elderly people. In the future, more in-depth studies in conjunction with new technologies are needed to explore mental health and real-time risk feedback for older people. </sec> <sec> <title>CLINICALTRIAL</title> Not applicable. </sec>
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,400 | 0,284 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».