Real-Time Nail-Biting Detection on a Smartwatch Using Three CNN Models Pipeline
Yazarlar (2)
Abdullah Alesmaeil
Karabük Üniversitesi, Türkiye
Karabük Üniversitesi, Türkiye
Doç. Dr. Eftal ŞEHİRLİ Karabük Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Computational Intelligence (Q3) | ||
| Dergi ISSN | 0824-7935 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2025 |
| Cilt / Sayı / Sayfa | 41 / 1 / – | DOI | 10.1111/coin.70020 |
| Makale Linki | https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70020 | ||
| UAK Araştırma Alanları |
Makine Öğrenmesi
Görüntü İşleme
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| Özet |
| Nail‐biting (NB) or onychophagia is a compulsive disorder that affects millions of people in both children and adults. It has several health complications and negative social effects. Treatments include surgical interventions, pharmacological medications, or additionally, it can be treated using behavioral modification therapies that utilize positive reinforcement and periodical reminders. Although it is the least invasive, such therapies still depend on manual monitoring and tracking which limits their success. In this work, we propose a novel approach for automatic real‐time NB detection and alert on a smartwatch that does not require surgical intervention, medications, or manual habit monitoring. It addresses two key challenges: First, NB actions generate subtle motion patterns at the wrist that lead to a high false‐positives (FP) rate even when the hand is not on the face. Second, is the challenge to run power‐intensive … |
| Anahtar Kelimeler |
| habit reversal therapy | human activity recognition | obsessive-compulsive disorders | onychophagia | trichotillomania |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 1 |