Academic Journal
Unobtrusive Cognitive Assessment in Smart-Homes: Leveraging Visual Encoding and Synthetic Movement Traces Data Mining
| العنوان: | Unobtrusive Cognitive Assessment in Smart-Homes: Leveraging Visual Encoding and Synthetic Movement Traces Data Mining |
|---|---|
| المؤلفون: | Samaneh Zolfaghari, Annica Kristoffersson, Mia Folke, Maria Lindén, Daniele Riboni |
| المصدر: | Sensors, Vol 24, Iss 5, p 1381 (2024) |
| بيانات النشر: | MDPI AG |
| سنة النشر: | 2024 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | trajectory mining, visual feature extraction, smart environments, machine learning, environmental sensors, ambient sensing, Chemical technology, TP1-1185 |
| الوصف: | The ubiquity of sensors in smart-homes facilitates the support of independent living for older adults and enables cognitive assessment. Notably, there has been a growing interest in utilizing movement traces for identifying signs of cognitive impairment in recent years. In this study, we introduce an innovative approach to identify abnormal indoor movement patterns that may signal cognitive decline. This is achieved through the non-intrusive integration of smart-home sensors, including passive infrared sensors and sensors embedded in everyday objects. The methodology involves visualizing user locomotion traces and discerning interactions with objects on a floor plan representation of the smart-home, and employing different image descriptor features designed for image analysis tasks and synthetic minority oversampling techniques to enhance the methodology. This approach distinguishes itself by its flexibility in effortlessly incorporating additional features through sensor data. A comprehensive analysis, conducted with a substantial dataset obtained from a real smart-home, involving 99 seniors, including those with cognitive diseases, reveals the effectiveness of the proposed functional prototype of the system architecture. The results validate the system’s efficacy in accurately discerning the cognitive status of seniors, achieving a macro-averaged F 1 -score of 72.22% for the two targeted categories: cognitively healthy and people with dementia. Furthermore, through experimental comparison, our system demonstrates superior performance compared with state-of-the-art methods. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1424-8220 |
| Relation: | https://www.mdpi.com/1424-8220/24/5/1381; https://doaj.org/toc/1424-8220; https://doaj.org/article/c17f25da4c5e4610ab81c35838d85024 |
| DOI: | 10.3390/s24051381 |
| الاتاحة: | https://doi.org/10.3390/s24051381 https://doaj.org/article/c17f25da4c5e4610ab81c35838d85024 |
| رقم الانضمام: | edsbas.34CE5208 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 14248220 |
|---|---|
| DOI: | 10.3390/s24051381 |