Mental well-being has always been a topic not much discussed by people. Mental health, psychological fitness and depression are still topics that people are not much comfortable talking about. The greater problem is that people don’t even realize the onset of mental health issues, until it gets too late. At such times, people usually resort to therapists, while a few resort to drugs, and a few also end up taking the wrong steps. In these times, when we talk of connected devices and internet of things, mental health is an area that awaits to be transformed completely, at least for the people who can afford the wearable health devices. Smart watches, smart sensors in phones and smart glasses can also be a wonderful team to bring in mental health analytics to transform the mental well-being sector.
Mental Health Analytics will be the new paradigm very soon as machine learning models scrutinize the real-time data generated by users of wearable health devices and live tracking of a person’s health becomes possible. People connected to the web will have more visibility into the parameters which are a reflection of the person’s state of mind at that moment. No wonder, proactive healing techniques will be more effective in such scenarios.
Real-time mental health tracking
The big idea in Mental Health Analytics relies on the wearable healthcare devices that people are wearing in large numbers these days. The adoption of smart watches, health monitors and healthcare apps bear a testimony to the growing preference for digital healthcare solutions in the market. These devices keep a track of parameters like breathing rate, signs of fidgeting, typing speed, sweating, pulse rate, frantic movement of limbs and posture of the body. Numerous such parameters go into the data model to predict the probabilities of anxiety, depression and psychological disorder.
These data points are monitored in real-time by the wearable devices and then relayed on to a central server that is accessible to the medical authorities or doctors. In case a person shows excess of sweating or higher pulse rate or unusual fidgeting behavior or all of them combined, the wearable devices will detect an anomaly and will identify them as signs of anxiety. Edge intelligence will bring analytics close to the edge and will perform most of the analytical processing close to the users. The analytical models on the cloud will perform deeper investigation for finding clues to some potential mental disorder. These data points will get stored in the Electronic Health Records (EHRs), which will be readily available for the doctors to have a look at. Obviously, the user will have to grant consent for access to the digital records.
Secure storage of the personal health data
The security of data storage of the health information is pivotal to the success of the mental health analytics paradigm. Data generated from the wearable healthcare devices must be stored immutably on a distributed ledger, so that the users and the doctors have an unaltered database of health records. Moreover, cybersecurity layers need to be added in order to render the data secure and immune to stealth. Encryption techniques, along with compliance of the data regulations in different regions, have to be adhered to. The users must always feel assured of the protection and privacy of their data, and their autonomy on the use of the health data for analytics and research purposes.
Instant alerts in case of disorders
Two types of alerts can be generated for the users – proactive and reactive. Proactive alerts are based on historical trend analysis. The predictive analytics models will keep churning the historical health data to derive insights and to detect any pattern that indicates development of certain symptoms of mental disorder. The frequency of anxious situations, the irregularity of pulse rate and the development of abnormal blood pressure can be indicative of an impending mental disorder. It can also highlight the adverse impact that the stressful situations may have on the user and can bring to the user’s notice the need to rein in the stressful situations. The doctors having access to this historical data will also be alerted of some imminent mental health crisis and the looming threats that accompany it. The doctor can then proactively reach out to the user with evidence, thereby initiating a proactive remedial therapy.
In case the wearable devices happen to detect any major anomaly in the health parameters of the users, an alert will be generated immediately to warn the users of crossing the threshold anxiety levels. Remedial measures will be initiated, like dimming of the lights in the room to an ambient level, cooling down of the room temperature and maybe even playing a soothing music that calms the nerves down. IoT will make all of it possible, by connecting the wearable health device to the appliances in offices and homes. At the same time, an app connected to the wearable will spring into action and will recommend therapeutic measures to the users. Actions like deep breathing, listening to relaxing music for 5 minutes or taking a power nap will be instrumental in beating anxiety levels, and protecting the body from its adverse effects.
Data sharing with employers
Employers can also benefit out of the application of mental health analytics. The concept of remote work has caught worldwide attention after the COVID-19 crisis. When employees are away from the office, it gets difficult to keep a track of the well-being of an employee and supervisors often end up not realizing if an employee is getting stressed. In case employees choose to share their electronic health data with the employers, the latter can keep a track of the mental well-being of the former and can also check if the employee is feeling stressed with the work assigned to him or her. This way, the supervisors will be able to better plan the assignments for their subordinates and will be able to maintain a motivated and happy workforce.
It is an altogether different discussion, however, whether the employees would like to share their personal health data with the employers. Moreover, the tolerable or comfortable level of anxiety is subjective to the personality of each individual. Different people have different thresholds of tolerance of mental pressure. A single threshold may not work for all kinds of people, as some may prefer to have a relaxed lifestyle while others may prefer to stress themselves in challenging assignments. Therefore, application of mental health analytics will depend a lot on consent and personalization.
Concluding thoughts
Wearable healthcare devices are new hinge around which the new paradigm of analytics shall revolve. Mental health is still a topic that is seldom discussed openly and it needs to become the center of attention for all health-conscious people. And in case people are skeptical to talk about their mental health to their friends and colleagues, then the wearable devices can provide a proper mental care by providing privacy and therapy without informing anyone else. It will assist people to deal with their mental well-being by themselves and in acute cases, take consultation of doctors who are well-equipped with the knowledge of historical health records of the person. Seeing the ubiquity of the wearable devices, it seems like this future is not too distant.
