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Up until two years ago, if someone would have asked me to contribute to an open blog about Bipolar Disorder, I probably would have declined. You see, the stigma attached to mental health concerns is real… and by living in my secret identity, I too was perpetuating this stigma. My secret Bipolar I was diagnosed when I was 20; that was over 25 years ago. At first, I did not tell my parents because I did not want anybody to think I was crazy, plus culturally Hispanic, mental health was not openly discussed as problems were only to be shared within close family; it was not the place of strangers. When I opened up to my parents, I do not think they really understood, but I was very sick and they were supportive, although the word “bipolar” was not used by them, until recently.
I would go on to finish my undergraduate degree, followed by graduate school while on medication with regular psychiatric care. I went on to get married and to work 10+ years in a leadership position, that is, until my condition worsened, plagued by various hospitalizations. Eventually, I had to stop working and drop out of a doctoral program I was a year into. It was a hard lesson to learn that I was not my work, and I was not my diagnosis. To cope, I turned to art. I had a collection of paintings and drawings; however, this is when I started to draw what I call my “Brain Art” – this art allowed me to express feelings and turned into a major coping method for me; allowing the chaos of my mind to find its voice. So, what changed now to reveal my secret identity? It took an open call for art two years ago by the Ryan Licht Sang Bipolar Foundation that asked the question, “What does it feel like to have Bipolar Disorder?” – I felt that I could submit some of my “Brain Art.” I first consulted with my mom, wondering if my parents would be ok if I submitted my art to this competition. Truth is, my parents had not seen my years of “Brain Art” – my doctors and some peers had seen it before – mom said she way ok with it; however, she told me to get ready to out myself as publicly having Bipolar Disorder. I decided to take a chance and submit my work; it turned out to be one of 20 pieces chosen to be shown in Chicago and Palm Beach that year – it really felt good and I came to realize that it was time to come out of the Bipolar Closet. This past year the Foundation hosted a retrospective show, selecting 20 artists from the last few years of these events and my work was chosen once again. It was this past October 2024 at the retrospective in Chicago that I met Dr. Alex Leow and subsequently learned of the BiAffect project. I downloaded the BiAffect3 app to my iPhone and began to wander around, curious to see how it works. I thought her area of research and expertise to be really impressive and interesting because the truth is, sometimes I do not know where my mood is headed; however, in a more primitive way, this is usually when I head to a box full of paper cuttings and make collages. My hands and mind guide me and the messages can be very telling of what I may or may not realize. But truth be told, sometimes I am not up to it. Now with the BiAffect3 app, I check in at least twice a day (sometimes more) answering simple questions relevant to my moods as well as “playing” two games tracking speed and accuracy. Along with the app, I am using the BiAffect3 keyboard for everything I write on my iPhone keyboard. Prior to using this app, I have always been a bit of a techie. I have spent plenty of time looking through other mood tracker apps, and they have not been fulfilling and do not track these mood changes in a very comprehensive manner; BiAffect3 knows Bipolar. When I joined the BiAffect3 app study, I shared it with my professionals – psychiatrist and psychologist. They too quickly found its value and asked about the graphs in subsequent visits. I usually see each doctor every two weeks and am treated with ECT every two weeks for now. In the life of Bipolar 1 – at least me personally – it can be hard to remember the last weeks’ moods or happenings of daily life, especially because I can be a rapid cycler. As I plot more data in the app I am starting to see a bigger picture. Included in the app, the “Learn” tab is informative and a good starting point for anyone to bring questions to their doctors. Now using the app, I am privy to more information about myself that can help not only my doctors, it can help me directly; allowing me to take charge and be more self-sufficient. Christina D. Encinosa
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 Imagine how a pianist’s fingers glide across the keys, each note reflecting their emotions and state of mind. Now, consider how your fingers interact with your phone’s keyboard every day. With texting becoming our primary form of communication, the keyboards on our phones have become as central to our lives as a piano is to a pianist. At BiAffect, we believe these everyday interactions hold the key to understanding our mental health. With BiAffect, we aim to provide unique insights into mental health through the analysis of typing dynamics on smartphones. Similar to what how a Fitbit helps track physical fitness, BiAffect tracks mental and emotional health—like a Fitbit for the brain. Our mission is to offer a non-intrusive, continuous method of monitoring mood and cognitive changes by analyzing how people interact with their keyboards. With the increasing preference for texting over talking, our phones have become essential to our daily communication. Many people spend significant time typing out messages, emails, posts, and other text rather than engaging in voice conversations or phone calls. This shift in communication style means that our keyboards are now central to how we express ourselves and connect with others. By analyzing our typing patterns, we can uncover valuable insights into our mental and emotional states, making it possible to track our well-being in a meaningful way. BiAffect began life as the prizewinning entry to the Mood Challenge for ResearchKit, and the team is led by Alex Leow, MD, PhD, Professor in Psychiatry, Biomedical Engineering, and Computer Science at the University of Illinois at Chicago, with ongoing technology development spearheaded by senior AI/ML/MLOps expert Theja Tulabandhula, PhD, AI researcher and software engineer Andrew Paparella, senior software engineer Shannon Young, and research specialist Faraz Hussain. BiAffect has been covered extensively in the news over the years, including in the Wall Street Journal, Rolling Stone, and IEEE Spectrum. Leveraging Keystroke Dynamics for Mental Health Insights BiAffect is based on the premise that typing patterns—how we interact with our keyboards—can reveal a wealth of information about our mental and emotional states. By continuously analyzing keystroke dynamics, we can detect subtle changes that may indicate mood shifts or cognitive fluctuations. Core Keystroke Dynamics Features Typing Speed Typing speed, measured by examining the statistical distribution of flight times, can reveal changes in processing speed, a key domain of cognition. Variations in typing speed can indicate different mental states. For example, a decrease in typing speed may be associated with depression or cognitive fatigue, while an increase could suggest heightened alertness or anxiety. Flight Time Flight time is the interval between consecutive key presses. Longer flight times can indicate hesitation or uncertainty, which may be linked to inattention, distraction, or cognitive overload. Shorter flight times can suggest increased urgency, anxiety, or impulsivity. Error Rates Error rates refer to the frequency of corrections and typos. Higher error rates can be indicative of cognitive stress, distractions, etc., and are commonly observed during severe depression. While individual error rates may vary, significant changes over time can provide additional context when analyzed alongside other keystroke dynamics. Key Hold Time Key hold time, or the duration a key is pressed, can provide insights into motor function and cognitive control. Prolonged key hold times may suggest motor impairments or cognitive slowing, while shorter hold times can indicate increased motor activity or restlessness. Accelerometer Data In addition to keystroke dynamics, BiAffect also incorporates accelerometer data from the user’s smartphone. This data helps capture physical movements and phone orientation information that can provide important context about the kinds of activities the user was engaged in, such as whether they were walking, standing, laying down, in a moving vehicle, etc. while typing on their phone.  Machine Learning Analysis The extracted features from keystroke dynamics and accelerometer data are fed into our machine learning models. We use a combination of supervised and unsupervised learning techniques to identify patterns in the data. Supervised learning models are trained on labeled datasets, where the mood or cognitive state of the user is known. Unsupervised learning models, on the other hand, help uncover hidden structures in the data, providing insights into previously unknown patterns.  Real-Time Monitoring and Feedback BiAffect provides a dashboard within the app where users can monitor their typing patterns and accelerometer data. This dashboard presents the analyzed data, helping users understand their mental health trends. By examining changes in their keystroke dynamics and active task scores on activities such as a Go/No-Go Reaction Time test and Trailmaking test, users can gain valuable insights into their mental state and take proactive steps to manage their well-being.
Conclusion At BiAffect, we are committed to advancing mental health monitoring through innovative technology. By leveraging various keystroke dynamics such as typing speed, flight time, error rates, key hold time, along with accelerometer data and active tasks, we provide valuable insights into mental health. Our custom keyboard plays a crucial role in this mission, integrating seamlessly into our app to capture and analyze these metrics with precision and efficiency. By continuing to refine our algorithms and expand our feature set, we aim to make BiAffect an indispensable resource for mental health management. We welcome you to download BiAffect and see how our pioneering use of keystroke dynamics can enhance your understanding of mental health. Our aim is to provide practical insights that can help you navigate your well-being.  Longtime BiAffect collaborator Dr. Michelle Chen chaired a symposium at the 2023 meeting of the International Neuropsychology Society in Taipei, Taiwan entitled “Smartphones as a window into everyday brain health: applications of keystroke dynamics, ecological momentary assessment, and accelerometry” featuring BiAffect Principal Investigator Dr. Alex Leow as discussant alongside fellow presenters Dr. Tammy Chung and Andrea Cladek.
 BiAffect Principal Investigator Dr. Alex Leow chaired a symposium at the 25th Annual Conference of the International Society for Bipolar Disorders in Chicago, IL on “Digital Phenotyping to Support Wellness in People With Bipolar Disorder” featuring fellow presenters Drs. Maria Faurholt-Jepsen and Debbie Huang.
BiAffect team member Claudia Vesel has been awarded a travel grant to present her research on "Diurnal Patterns as Evidenced by over Eleven Million Smartphone Keystrokes During Daily Usage" at the 2019 NNDC Annual Conference, to be held September 24-25 in Ann Arbor, MI.
 On the 30th birthday of the World Wide Web, BiAffect's Dr. Alex Leow speaks at Chicago AI Days about the use of artificial intelligence in measuring mood.
BiAffect chosen by the NIH to present at the 2018 MD2K mHealthHUB Technology Showcase on June 4, 2018. Drs. Ajilore and Leow are excited to demonstrate BiAffect as an open science research tool to improve the reliability and validity of passive sensing using keyboard metadata.
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