In 2020, over 40,000 people in the United States committed suicide and over a million attempted it . Every 40 seconds, a person will die by their own hand globally . A sobering thought, isn’t it?
But is there a way we could predict a mental health crisis and suicide attempts by detecting and measuring a person’s mental health?
Have you noticed how when you get angry, your heart starts beating faster, or when you are stressed, you might sweat? This happens because several body signals (biosignals) are strongly correlated with your emotional status.
Use of remote monitoring technologies in the healthcare sector have boomed in recent years, while mental health technology has lagged behind. One of the single biggest problems facing the sector is the lack of continuous objective data. So far, there hasn’t been a diagnostic or measurement tool that can objectively and continuously monitor and quantify a person’s emotional state like we can measure our temperature with a thermometer or examine blood work with a glucose meter.
Based on decades of research in the field of Affective Technology, Feel has provided a breakthrough. It is the only mental health wearable device that continually monitors and detects a variety of physiological signals to understand and quantify the changes to a person’s emotional state, allowing objective data to be used for the very first time in mental health support & care.
There is no single reason why someone decides to take their own life. It is generally a combination of many factors which could include mental illness, stress, substance misuse, chronic pain or illness, feelings of hopelessness, or feeling like a burden.
Over the last few decades, neuroscience research has shown that emotions are created by our brain and involve the entire nervous system, more specifically, the Autonomic Nervous System (ANS). This is the control system. This is what causes your heart to beat faster and your muscles to tense when your body enters the “fight or flight” mode. These sensory measurements can function as digital biomarkers and be used as an indicator of a particular disease state, and research  has shown that certain biomarkers have the strongest correlation with a person’s emotional status, including depressive and other moodstates. As such, this could help in predicting crisis & support clinicians to intervene in a timely and effective way.
One of these measures is electrodermal activity (EDA), which is a measure of how the skin’s electrical activity varies according to the amount of sweat produced. In fact, research studies [2 to 8] have observed that individuals with a history of suicidal behavior demonstrate low electrodermal activity (EDA) at the baseline and in response to habituation tasks.
This is quite significant as it opens the path to use such biomarkers to run better research around medication and improve outcomes for patients.
Using objective data in psychiatric drug assessments and clinical trials will pave the way for the discovery of novel drug treatments for mental illness, improve medication adherence, and increase the effectiveness of existing treatments. The Feel Emotion Sensor’s continual emotion monitoring could help detect signs of depression onset, treatment resistance or even suicidal tendencies and provide early warning and support to help pharma companies run better research for depression either as a precursor to or alongside depression medication trials and assessments, with measurements working as validated digital biomarkers. This technology was created in our efforts to develop digital biomarkers and therapeutics to bring objective, passive, and continuous measurement and data to reinvent the way we diagnose, manage, and care for mental health.
Feel Therapeutics was recently selected as an awardee of the prestigious Janssen Digital Solutions QuickFire Challenge that selected solutions in the mental health field with the potential to scale within the next five years. Janssen, the pharmaceutical company of Johnson & Johnson, will help Feel Therapeutics with mentoring, commercial expertise and resources needed to maximize the potential of developing new solutions that can accelerate the pace of digital biomarkers and therapeutics being adopted in the industry.
As part of the program, Feel Therapeutics and Janssen will identify innovative projects where Feel can apply their innovative and proprietary technology to develop and explore various biomarkers extracted from biosignals related to mental health. It will be valuable to focus on the negative affective states and analyze how these markers change among various emotional experiences and mental health conditions and how we can target therapeutic interventions to get the best outcomes. The analysis of such data can validate and complement a pharmaceutical company’s work, support “beyond the pill” strategies, and bring more effective medications and holistic solutions to market faster.
By providing objective data and quantifiable insights, emotion recognition technology can allow pharma researchers and medical affairs teams to predict, prevent, and better treat depression and other mood disorders — as standalone or comorbid with another chronic condition — with the appropriate medication.
The collection and use of objective data could also help reduce waiting times, avoid misdiagnosis of mental health issues, and give mental health experts the tools to provide more meaningful and personalized care and support. Most importantly, though, it could provide real-time identification and timely intervention in an unobtrusive manner that can help patients suffer less and maintain a healthy mental state.
This could be a major breakthrough and change mental health care as we know it!
 Suicide Facts and Resources. Innerbody. Retrieved from https://www.innerbody.com/suicide-facts-resources
 Kreibig, S. D. (2010). Autonomic nervous system activity in emotion: A review. Biological Psychology, 84(3), 394–421.
 Shu, L., Xie, J., Yang, M., Li, Z., Li, Z., Liao, D., Xu, X., & Yang, X. (2018). A Review of Emotion Recognition Using Physiological Signals. Sensors, 18(7), 2074.
 Kim, K.H., Bang, S.W. & Kim, S.R. (2004). Emotion recognition system using short-term monitoring of physiological signals. Med. Biol. Eng. Comput. Vol 42, pp. 419–427.
 Edman, G., Åsberg, M., Levander, S., & Schalling, D. (1986). Skin conductance habituation and cerebrospinal fluid 5-hydroxyindoleacetic acid in suicidal patients. Archives of General Psychiatry, 43(6), 586–592.doi:10.1001/archpsyc.1986.01800060080010
 Jandl, M., Steyer, J., & Kaschka, W. P. (2010). Suicide risk markers in major depressive disorder: A study of electrodermal activity and event-related potentials. Journal of Affective Disorders, 123(1–3), 138–149.doi:10.1016/j.jad.2009.09.011
 Sarchiapone, M., Gramaglia, C., Iosue, M., Carli, V., Mandelli, L., Serretti, A., Marangon, D., & Zeppegno, P. (2018). The association between electrodermal activity (EDA), depression and suicidal behaviour: A systematic review and narrative synthesis. BMC Psychiatry, 18(22) 1–27. doi: 10.1186/s12888–017- 1551–4
Thorell, L. (2009). Valid electrodermal hyporeactivity for depressive suicidal propensity offers links to cognitive theory. Acta Psychiatrica Scandinavica, 119(5), 338–349. doi:10.1111/j.1600–0447.2009.01364.x
 Thorell, L. H., Wolfersdorf, M., Straub, R., Steyer, J., Hodgkinson, S., Kaschka, W. P., & Jandl, M. (2013). Electrodermal hyporeactivity as a trait marker for suicidal propensity in uni- and bipolar depression. Journal of Psychiatric Research, 47(12), 1925–1931. doi:10.1016/j.jpsychires.2013.08.017
 Wolfersdorf, M., Straub, R., Barg, T., Keller, F., & Kaschka, W. P. (1999). Depressed inpatients, electrodermal reactivity, and suicide — a study about psychophysiology of suicidal behavior. Archives of Suicide Research, 5(1), 1–10. doi:10.1023/A:1009618520224