Analytical Study Serving Technical Features Extraction and Classification for most recent Smartphone-based Sleep Monitoring Applications
Year: 2024
Type: article
Abstract: Purpose: In this study; the author explains and shows the importance of selection and extraction the technical features of Smartphones' apps regarding sleep-monitoring and sleep-analysis, and the technical features' selection and extraction impact on simplifying the features classification based on the most important sleep disorders screening and diagnosis symptoms. Methods: by taking an in-depth analytical survey study and screening for most recent sleep-monitoring apps through the period from June -to- September 2024, and enumerating the common technical features of the sleepmonitoring apps related to the screened symptoms of sleep disorders and sleep-analysis studies. The study's author examined 145 of the most recent sleep-monitoring apps, and extracted the common technical features related to the most concerning sleep-disorder screened symptoms, then classifies the extracted features into categories. Moreover, the author conducted a statistical analysis for the extracted features to measure the number and percentage of the most recent sleep-monitoring apps that offer those extracted and classified technical features. Results: a total of 145 most recent sleep-monitoring related apps were examined at first in the study which took place during the period from June – to - September 2024 focusing on 22 major technical features of sleepmonitoring apps, 35 apps (24.14%) were excluded from the study due to irrelevant design purposes, while 12 apps (8.27%) were excluded for duplication in the two major app stores (Apple Store and Google Play), then another 18 apps (12.41%) were excluded due to low usage and low rating during study period. At last, another 19 apps (13.1%) were excluded from the study because they did not meet the designed requirement values of the sensors' threshold-based features or pattern recognition-based features. Finally, 61 apps (42.07%) satisfied all the applications' inclusion criteria, and statistical model built through the extracted technical features in the study. Conclusions: despite that there are hundreds of approved smartphones' sleep-monitoring and analysis applications; this analytical study evaluates, examines and analyzes the major common 22 technical features in 61 of the most recent apps with users' most highly rated apps in Apple and Google play stores with several advantages and beneficial features, including smart alarms and sleep aids. However, an in-depth content review of apps that met the inclusion criteria revealed that sleep-monitoring applications can utilize more improvements in technical features design and implementation
Author: Nadir M. Abdelaziz
Institution: Jazan University
Language: English
Topic: Sleep and related disorders
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: bronze
Funder: Jazan University
OpenAlex ID: W4405079154