Depression is a common mental illness characterized by sadness, lack of interest, or pleasure. According to the DSM-5, there are nine symptoms, from which an individual must present 4 or 5 in the last two weeks to fulfill the diagnosis criteria of depression. Nevertheless, the common methods that health care professionals use to assess and monitor depression symptoms are face-to-face questionnaires leading to time-consuming or expensive methods. On the other hand, smart homes can monitor householders' health through smart devices such as smartphones, wearables, cameras, or voice assistants connected to the home. Although the depression disorders at smart homes are commonly oriented to the senior sector, depression affects all of us. Therefore, even though an expert needs to diagnose the depression disorder, questionnaires as the PHQ-9 help spot any depressive symptomatology as a pre-diagnosis. Thus, this paper proposes a three-step framework; the first step assesses the nine questions to the end-user through ALEXA or a gamified HMI. Then, a fuzzy logic decision system considers three actions based on the nine responses. Finally, the last step considers these three actions: continue monitoring through Alexa and the HMI, suggest specialist referral, and mandatory specialist referral.
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http://dx.doi.org/10.3390/s21237864 | DOI Listing |
JMIR Aging
December 2024
Department of Engineering, King's College London, London, United Kingdom.
Background: Previous studies have explored how sensor technologies can assist in in the detection, recognition, and prevention of subjective loneliness. These studies have shown a correlation between physiological and behavioral sensor data and the experience of loneliness. However, little research has been conducted on the design requirements from the perspective of older people and stakeholders in technology development.
View Article and Find Full Text PDFHeliyon
August 2024
Solar Energy Research Cell (SERC), School of Electrical Engineering, Vellore Institute Technology, Vellore, Tamil Nadu-632014, India.
In the present day electricity demand, demand response programs support mitigating the power demand and help to improve stability. Within this framework, the Home Energy Management System (HEMS) plays a critical role in optimizing energy consumption patterns by redistributing loads from peak to off-peak hours, thereby subsequently contributing to grid stability. The existing HEMS model often fails to simultaneously address the three important issues.
View Article and Find Full Text PDFJMIR Form Res
December 2024
Department of Psychology and Health Studies, College of Arts and Science, University of Saskatchewan, Sasktoon, SK, Canada.
Background: Examining ways to support persons with dementia and their caregivers to help minimize the disease's impact on individuals, families, and society is critical. One emerging avenue for support is technology (eg, smartphones and smart homes).
Objective: Given the increasing presence of technology in caregiving, it is pertinent to appreciate whether and how technology can be most useful to a care partner's everyday life.
J Gerontol A Biol Sci Med Sci
December 2024
Marcus Institute for Aging Research, Boston, MA, USA.
Background: Climate change is expected to disrupt weather patterns across the world, exposing older adults to more intense and frequent periods of hot weather. Meanwhile, lab-based studies have established a causal relationship between ambient temperature and cognitive abilities, suggesting the expected rise in temperature may influence older adults' cognitive functioning. Nevertheless, it is not clear whether, and to what extent, the temperature variations in older adults' own homes - which unlike lab settings is under their control - influence their cognitive functioning.
View Article and Find Full Text PDFPeerJ Comput Sci
October 2024
Joint Laboratory for International Cooperation of the Special Optical Fiber and Advanced Communication, Shanghai University, Shanghai, China.
A Wi-Fi-sensing gesture control system for smart homes has been developed based on a theoretical investigation of the Fresnel region sensing model, addressing the need for non-contact gesture control in household environments. The system collects channel state information (CSI) related to gestures from Wi-Fi signals transmitted and received by network cards within a specific area. The collected data undergoes preprocessing to eliminate environmental interference, allowing for the extraction of complete gesture sets.
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