Mental Health Monitoring : A new feature of IPhone
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Mental Health Monitoring : A new feature of IPhone

The advent of technology has been rising to become more user-friendly nowadays, as a new feature is added to the list of essential features of the iPhone. According to the research in Wall street journal, user’s minute data like sleep analysis, way of typing, exercise routines can help in spotting the behavior associated with the symptoms of mental illness like anxiety, depression, and other disorders. Altogether, now iPhone can read and analyze the facial expression and heart respiration rates without breaching the privacy of the user by not sending the data to the servers. The features are well-backed by the research conducted by the University of California, Los Angeles that is exploring the status of stress, anxiety, and depression via apple watch and iPhone data of 3000 volunteers who participated in the study this year, prior this the pilot study had been conducted for 150  volunteers in begging of 2020.

Another project has been running under the pharmaceutical firm Biogen who has been on the route of developing the software that will track the user’s cognitive function and spot the cognitive impairment that can develop into Alzheimer’s disease. In the study, 20000 participants have tracked out of which half of the sample has the risk of developing cognitive impairment.

Not only limited to tracking the user’s symptoms but the software is designed to detect the symptoms and warn the user if signs of mental illness are found to take necessary steps to enhance the quality of life. The announced study by Apple and UCLA in 2020 shared the plan to compare the data from iPhone and Watch sensors with questionnaires provided to the volunteers regarding their current feelings, level of stress hormone from the hair follicles of the participants, the company is currently in the early stages of the establishment of this feature.

The current research has its base on the proven study that people with some mental illnesses use devices differently than other normal populations, however, it is not yet clear that such algorithms can detect mental conditions accurately. There is hope for developing the technology in certain ways to help ease the problems and early detection.

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