Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness.

Background: Recent studies on acute mountain sickness (AMS) have used fixed-location and fixed-time measurements of environmental and physiological variable to determine the influence of AMS-associated factors in the human body. This study aims to measure, in real time, environmental conditions and physiological variables of participants in high-altitude regions to develop an AMS risk evaluation model to forecast prospective development of AMS so its onset can be prevented.

Results: Thirty-two participants were recruited, namely 25 men and 7 women, and they hiked from Cuifeng Mountain Forest Park parking lot (altitude: 2300 m) to Wuling (altitude: 3275 m).

Data Analytics of a Wearable Device for Heat Stroke Detection.

When exercising in a high-temperature environment, heat stroke can cause great harm to the human body. However, runners may ignore important physiological warnings and are not usually aware that a heat stroke is occurring. To solve this problem, this study evaluates a runner's risk of heat stroke injury by using a wearable heat stroke detection device (WHDD), which we developed previously.

Systematic node management mechanism using ZigBee-based real-time vital sign information monitoring system to manage large numbers of patients.

Background: Local hospitals must deal with large numbers of patients during mass casualty incidents, and the wireless sensor networks (WSNs) can help in these situations by monitoring vital signs. Conventional ZigBee nodes can obtain the ID of a device by assigning a unique 16-bit short address or by burning firmware into an IC. These methods tend to complicate node management and lack portability.

Development of an ease-of-use remote healthcare system architecture using RFID and networking technologies.

The study aims to provide an ease-of-use approach for senior patients to utilize remote healthcare systems. An ease-of-use remote healthcare system (RHS) architecture using RFID (Radio Frequency Identification) and networking technologies is developed. Specifically, the codes in RFID tags are used for authenticating the patients' ID to secure and ease the login process.