There are an increased number of patients and elderly people who are alone worldwide. These people are often treated in –home and at times enter into a critical situation that may require help. The facial expressions are widely researched and employed to classify people emotional states. Such facial expressions have already been studied to determine the emotional health of an individual which, in turn, can be used as an important symptom for the diagnosis of various dis-eases such as: schizophrenia, depression, autism, bipolar disorder. Capturing facial expressions over a certain period of time can give an idea of to what extent the patient is feeling pain and can enable nurse/family members to decide the feelings of the patient and to provide necessary assistance. This research work describes the design of a system for continuous monitoring of patients/elderly people through person identification and emotion recognition to provide healthcare in home environments in an automatic way through an IoT infrastructure without human intervention. Using smart camera the patient’s images are captured continuously and transmitted to the decision maker (laptop/desktop) for person identification. Once the patient is identified, he/she is monitored continuously for emotion recognition through facial expressions and the detected emotions are stored in the cloud. When abnormal condition is detected, an alert message is sent to the care taker/nurse.

E-health, Remote Monitoring, Person Identification, Emotion Recognition, Internet of Things

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