  The Medical Internet of Things, a recent technological advancement in
medicine, is incredibly helpful in providing real-time monitoring of health
metrics. This paper presents a non-invasive IoT system that tracks patients'
emotions, especially those with autism spectrum disorder. With a few affordable
sensors and cloud computing services, the individual's heart rates are
monitored and analyzed to study the effects of changes in sweat and heartbeats
per minute for different emotions. Under normal resting conditions of the
individual, the proposed system could detect the right emotion using machine
learning algorithms with a performance of up to 92% accuracy. The result of the
proposed approach is comparable with the state-of-the-art solutions in medical
IoT.
