University+of+Michigan
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A Way for Smartwatches to Detect Depression Risks Devised by KAIST and U of Michigan Researchers
- A international joint research team of KAIST and the University of Michigan developed a digital biomarker for predicting symptoms of depression based on data collected by smartwatches
- It has the potential to be used as a medical technology to replace the economically burdensome fMRI measurement test
- It is expected to expand the scope of digital health data analysis
The CORONA virus pandemic also brought about a pandemic of mental illness. Approximately one billion people worldwide suffer from various psychiatric conditions. Korea is one of more serious cases, with approximately 1.8 million patients exhibiting depression and anxiety disorders, and the total number of patients with clinical mental diseases has increased by 37% in five years to approximately 4.65 million. A joint research team from Korea and the US has developed a technology that uses biometric data collected through wearable devices to predict tomorrow's mood and, further, to predict the possibility of developing symptoms of depression.
< Figure 1. Schematic diagram of the research results. Based on the biometric data collected by a smartwatch, a mathematical algorithm that solves the inverse problem to estimate the brain's circadian phase and sleep stages has been developed. This algorithm can estimate the degrees of circadian disruption, and these estimates can be used as the digital biomarkers to predict depression risks. >
KAIST (President Kwang Hyung Lee) announced on the 15th of January that the research team under Professor Dae Wook Kim from the Department of Brain and Cognitive Sciences and the team under Professor Daniel B. Forger from the Department of Mathematics at the University of Michigan in the United States have developed a technology to predict symptoms of depression such as sleep disorders, depression, loss of appetite, overeating, and decreased concentration in shift workers from the activity and heart rate data collected from smartwatches.
According to WHO, a promising new treatment direction for mental illness focuses on the sleep and circadian timekeeping system located in the hypothalamus of the brain, which directly affect impulsivity, emotional responses, decision-making, and overall mood.
However, in order to measure endogenous circadian rhythms and sleep states, blood or saliva must be drawn every 30 minutes throughout the night to measure changes in the concentration of the melatonin hormone in our bodies and polysomnography (PSG) must be performed. As such treatments requires hospitalization and most psychiatric patients only visit for outpatient treatment, there has been no significant progress in developing treatment methods that take these two factors into account. In addition, the cost of the PSG test, which is approximately $1000, leaves mental health treatment considering sleep and circadian rhythms out of reach for the socially disadvantaged.
The solution to overcome these problems is to employ wearable devices for the easier collection of biometric data such as heart rate, body temperature, and activity level in real time without spatial constraints. However, current wearable devices have the limitation of providing only indirect information on biomarkers required by medical staff, such as the phase of the circadian clock.
The joint research team developed a filtering technology that accurately estimates the phase of the circadian clock, which changes daily, such as heart rate and activity time series data collected from a smartwatch. This is an implementation of a digital twin that precisely describes the circadian rhythm in the brain, and it can be used to estimate circadian rhythm disruption.
< Figure 2. The suprachiasmatic nucleus located in the hypothalamus of the brain is the central biological clock that regulates the 24-hour physiological rhythm and plays a key role in maintaining the body’s circadian rhythm. If the phase of this biological clock is disrupted, it affects various parts of the brain, which can cause psychiatric conditions such as depression. >
The possibility of using the digital twin of this circadian clock to predict the symptoms of depression was verified through collaboration with the research team of Professor Srijan Sen of the Michigan Neuroscience Institute and Professor Amy Bohnert of the Department of Psychiatry of the University of Michigan.
The collaborative research team conducted a large-scale prospective cohort study involving approximately 800 shift workers and showed that the circadian rhythm disruption digital biomarker estimated through the technology can predict tomorrow's mood as well as six symptoms, including sleep problems, appetite changes, decreased concentration, and suicidal thoughts, which are representative symptoms of depression.
< Figure 3. The circadian rhythm of hormones such as melatonin regulates various physiological functions and behaviors such as heart rate and activity level. These physiological and behavioral signals can be measured in daily life through wearable devices. In order to estimate the body’s circadian rhythm inversely based on the measured biometric signals, a mathematical algorithm is needed. This algorithm plays a key role in accurately identifying the characteristics of circadian rhythms by extracting hidden physiological patterns from biosignals. >
Professor Dae Wook Kim said, "It is very meaningful to be able to conduct research that provides a clue for ways to apply wearable biometric data using mathematics that have not previously been utilized for actual disease management." He added, "We expect that this research will be able to present continuous and non-invasive mental health monitoring technology. This is expected to present a new paradigm for mental health care. By resolving some of the major problems socially disadvantaged people may face in current treatment practices, they may be able to take more active steps when experiencing symptoms of depression, such as seeking counsel before things get out of hand."
< Figure 4. A mathematical algorithm was devised to circumvent the problems of estimating the phase of the brain's biological clock and sleep stages inversely from the biodata collected by a smartwatch. This algorithm can estimate the degree of daily circadian rhythm disruption, and this estimate can be used as a digital biomarker to predict depression symptoms. >
The results of this study, in which Professor Dae Wook Kim of the Department of Brain and Cognitive Sciences at KAIST participated as the joint first author and corresponding author, were published in the online version of the international academic journal npj Digital Medicine on December 5, 2024. (Paper title: The real-world association between digital markers of circadian disruption and mental health risks) DOI: 10.1038/s41746-024-01348-6
This study was conducted with the support of the KAIST's Research Support Program for New Faculty Members, the US National Science Foundation, the US National Institutes of Health, and the US Army Research Institute MURI Program.
2025.01.20 View 3319 -
Professor Sukyung Park Named Presidential Science and Technology Adviser
Professor Sukyung Park from the Department of Mechanical Engineering was appointed as the science and technology adviser to the President Jae-in Moon on May 4. Professor Park, at the age of 47, became the youngest member of the president’s senior aide team at Chong Wa Dae.
A Chong Wa Dae spokesman said on May 4 while announcing the appointment, “Professor Park, a talent with a great deal of policymaking participation in science and technology, will contribute to accelerating the government’s push for science and technology innovation, especially in the information and communications technology (ICT) sector.”
Professor Park joined KAIST in 2004 as the first female professor of mechanical engineering. She is a biomechanics expert who has conducted extensive research on biometric mechanical behaviors. Professor Park is also a member of the KAIST Board of Trustees. Before that, she served as a senior researcher at the Korea Institute of Machinery and Materials (KIMM) as well as a member of the Presidential Advisory Council on Science and Technology.
After graduating from Seoul Science High School as the first ever two-year graduate, Professor Park earned a bachelor and master’s degrees in mechanical engineering at KAIST. She then finished her Ph.D. from the University of Michigan.
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2020.05.06 View 13034 -
A graduating student speaks about "hope" for many disabled people who dare to have a dream of becoming a scientist.
Dong-Won Kim, a graduate student of the Mechanical Engineering Department, KAIST, will leave for the US at the end of this month to further pursue his advanced degree at University of Michigan (UM) in Ann Harbor. He has completed his master’s program at KAIST this summer, specializing in rehabilitation engineering.
Mr. Kim was born with cerebral palsy, which made him difficult to talk and use his hands. Notwithstanding the obstacles, he went through the regular school system and earned a master’s degree offered by one of the toughest universities in Korea.
When asked about what was the most difficult thing to study, he said with a gentle smile that “other than taking him a longer time to solve a math problem because of his weak hand muscle, he doesn’t have any difficulties.”
“Of course, people around me helped me a lot, but I tried to maintain my confidence in me and did my best so as not to disappoint my family and friends who have supported me,” Mr. Kim added.
Professor Pyung-Hoon Chang of the Mechanical Engineering Department, who was an adviser to Mr. Kim, recalled,
“Dong-Won has been a great student; I was quite impressed with his intellectual vigor and academic passion. He got along well with his peer students and had always positive and can-do attitude. I’m really pleased to see him graduate, given the tough situation he’s been in. He sets an inspiring role model who overcame difficulties and achieved great accomplishments.”
Mr. Kim hopes that universities including KAIST improve their educational environment to adopt friendlier policies toward the people with disabilities so that more of them can be offered an opportunity to become a scientist or engineer.
He will study medical engineering at University of Michigan—through his doctoral study, he wishes to identify causes and improvements of disabilities suffered by people and become an expert in rehabilitation.
Mr. Kim also donated 1 million won to KAIST out of his appreciation for the support he had received during his stay at the school. He said, “Although this is a small amount, I’d like to “thank you” for the members of KAIST community including its faculty and staff who have encouraged me to finish the study. If possible, I’d like to make a greater contribution in the future, and to that end, I’ll study harder and try to become the person whom I have planned for.”
Upon hearing about his generosity, President Nam Pyo Suh said, “The gift is so wonderful because it was given to us from one of our students. I wish him great success in his future study and will look forward to having his valuable contributions to our school and the nation.”
2010.08.17 View 11378