Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Nov 24;23(23):9394.
doi: 10.3390/s23239394.

Consistent Healthcare Safety Recommendation System for Preventing Contagious Disease Infections in Human Crowds

Mohammed Amoon  1 , Torki Altameem  1 , Mohammed Hashem  2
Affiliations

Consistent Healthcare Safety Recommendation System for Preventing Contagious Disease Infections in Human Crowds

Mohammed Amoon et al. Sensors (Basel). .

Abstract

The recent impact of COVID-19, as a contagious disease, led researchers to focus on designing and fabricating personal healthcare devices and systems. With the help of wearable sensors, sensing and communication technologies, and recommendation modules, personal healthcare systems were designed for ease of use. More specifically, personal healthcare systems were designed to provide recommendations for maintaining a safe distance and avoiding contagious disease spread after the COVID-19 pandemic. The personal recommendations are analyzed based on the wearable sensor signals and their consistency in sensing. This consistency varies with human movements or other activities that hike/cease the sensor values abruptly for a short period. Therefore, a consistency-focused recommendation system (CRS) for personal healthcare (PH) was designed in this research. The hardware sensing intervals for the system are calibrated per the conventional specifications from which abrupt changes can be observed. The changes are analyzed for their saturation and fluctuations observed from neighbors within the threshold distance. The saturation and fluctuation classifications are performed using random forest learning to differentiate the above data from the previously sensed healthy data. In this process, the saturated data and consistency data provide safety recommendations for the moving user. The consistency is verified for a series of intervals for the fluctuating sensed data. This alerts the user if the threshold distance for a contagious disease is violated. The proposed system was validated using a prototype model and experimental analysis through false rates, data analysis rates, and fluctuations.

Keywords: contagious disease; personal healthcare; random forest; wearable sensor.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Illustration of density distribution and drop analysis.
Figure 2
Figure 2
Structure of consistency-focused recommendation system.
Figure 3
Figure 3
Graphical analysis of sensing fluctuation from real-time data.
Figure 4
Figure 4
Classification analysis for abrupt change detection.
Figure 5
Figure 5
Correlation process of post classification.
Figure 6
Figure 6
Analysis of correlation and normalization outcomes.
Figure 7
Figure 7
Process of violation detection and alert.
Figure 8
Figure 8
Comparative analysis of false rate.
Figure 9
Figure 9
Comparative analysis of fluctuations.
Figure 10
Figure 10
Comparative analysis of data analysis rate.
Figure 11
Figure 11
Comparative analysis of recommendation ratio.
Figure 12
Figure 12
Comparative analysis of consistency check.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Mehmood I., Li H., Qarout Y., Umer W., Anwer S., Wu H., Hussain M., Fordjour Antwi-Afari M. Deep Learning-Based Construction Equipment Operators’ Mental Fatigue Classification Using Wearable EEG Sensor Data. Adv. Eng. Inform. 2023;56:101978. doi: 10.1016/j.aei.2023.101978. - DOI
    1. Geng Y., Cao R., Innocent M.T., Hu Z., Zhu L., Wang L., Xiang H., Zhu M. A High-Sensitive Wearable Sensor Based on Conductive Polymer Composites for Body Temperature Monitoring. Compos. Part A Appl. Sci. Manuf. 2022;163:107269. doi: 10.1016/j.compositesa.2022.107269. - DOI
    1. de Fazio R., Giannoccaro N.I., Carrasco M., Velazquez R., Visconti P. Wearable Devices and IoT Applications for Symptom Detection, Infection Tracking, and Diffusion Containment of the COVID-19 Pandemic: A Survey. Front. Inf. Technol. Electron. Eng. 2021;22:1413–1442. doi: 10.1631/FITEE.2100085. - DOI
    1. Kouis P., Michanikou A., Anagnostopoulou P., Galanakis E., Michaelidou E., Dimitriou H., Matthaiou A.M., Kinni P., Achilleos S., Zacharatos H., et al. Use of Wearable Sensors to Assess Compliance of Asthmatic Children in Response to Lockdown Measures for the COVID-19 Epidemic. Sci. Rep. 2021;11:5895. doi: 10.1038/s41598-021-85358-4. - DOI - PMC - PubMed
    1. Lim W.J., Abdul Ghani N.M. COVID-19 Mandatory Self-Quarantine Wearable Device for Authority Monitoring with Edge AI Reporting & Flagging System. Health Technol. 2022;12:215–226. doi: 10.1007/s12553-021-00631-w. - DOI - PMC - PubMed

LinkOut - more resources