Many aspects of psychiatry are not exact sciences. Diagnosis and monitoring of various disorders still depends on subjective observation and patient interviews conducted by trained practitioners. A new study published in the IEEE Journal of Biomedical and Health Informatics reveals that wearable devices can be effective in monitoring and recognizing four different clinical mood states in patients with bipolar disorder.
The researchers suggest that biometric data on heart and breathing rates and on body posture could correlate with different moods. In their article, “Wearable Monitoring for Mood Recognition in Bipolar Disorder based on History-Dependent Long-Term Heart Rate Variability Analysis,” they report that using heart rate data alone, they were able to distinguish between four moods: depression, mixed state, hypomania, and euthymia. They conducted trials with eight patients and gathered more than 400 hours of data. Their system was able to accurately identify a patient’s mood state more than 95% of the time.
This has some intriguing implications for wearable Health Tech devices in psychiatric applications. As with other fitness, health, and medical applications, the ability to monitor a patients body data continuously over extended periods of time can create a valuable collection of information that can reveal correlations between certain body metrics and mental states. This could have implications for everything from using medications more sparingly and effectively, as well as coming up with alternative treatments such as notifying a patient or caregiver of a trend or situation so that corrective action can be taken promptly.