Scientific Foundations of Mood & Speech Tracking 

Clinical rating scales are the gold standard in psychology and psychiatry for assessing symptoms and their severity. These structured questionnaires, like the Young Mania Rating Scale (YMRS) and the Montgomery-Åsberg Depression Rating Scale (MADRS), are widely used by clinicians and regulatory agencies like the FDA to evaluate symptom severity and treatment effectiveness. 

While physical conditions like diabetes have precise biomarkers, such as blood sugar levels, mood disorders rely on clinical rating scales to quantify symptoms. Over decades, thousands of assessments using YMRS and MADRS have established clear thresholds for when mood signals deviate from normal variability into more concerning territory. 

How Mind Numbers Leverages Clinical Science 
Mind Numbers analyzes speech recordings to detect and quantify mood signals based on the subcategories defined by YMRS and MADRS. Using advanced algorithms, it evaluates language patterns, emotional content, topics, and tone, providing a comprehensive mood assessment. Results are categorized into five zones: very low, low, balanced, high, and very high. These zones align with clinical insights, helping users understand when their mood may be shifting outside the balanced range. 

Why It Matters 
If mood remains outside the balanced zone for more than a day or two, it will be important to review other factors like sleep, activity, and routine to see if there are similar mood indicators that you need to address. 

Regular Tracking Without the Hassle 
Mind Numbers eliminates the need for tedious daily questionnaires by automating mood tracking. While individual readings aren’t definitive, trends and changes over time provide valuable insights. Combined with simultaneous monitoring of sleep, activity, and routine, these insights empower individuals to stay proactive in managing their health. 

Relevant publications 

1. Lukasiewicz, M., Gerard, S., Besnard, A., Falissard, B., Perrin, E., Sapin, H., Tohen, M., Reed, C., & The EMBLEM Study Group. (2013). Young Mania Rating Scale: How to interpret the numbers? Determination of a severity threshold and of the minimal clinically significant difference in the EMBLEM cohort. International Journal of Methods in Psychiatric Research, 22(1), 46–58. https://doi.org/10.1002/mpr.1379 

2. Zimmerman, M., Posternak, M. A., & Chelminski, I. (2004). Defining remission on the Montgomery–Åsberg Depression Rating Scale. Journal of Clinical Psychiatry, 65(2), 163–168. https://doi.org/10.4088/JCP.v65n0205 

3. Morriss R. The early warning symptom intervention for patients with bipolar affective disorder. Advances in Psychiatric Treatment. 2004;10(1):18-26. doi:10.1192/apt.10.1.18 

4. Anmella G, De Prisco M, Joyce JB, Valenzuela-Pascual C, Mas-Musons A, Oliva V, Fico G, Chatzisofroniou G, Mishra S, Al-Soleiti M, et al. Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results. Journal of Clinical Medicine. 2024; 13(17):4997. https://doi.org/10.3390/jcm13174997 5. Nierenberg AA, Agustini B, Köhler-Forsberg O, et al. Diagnosis and Treatment of Bipolar Disorder: A Review. JAMA. 2023;330(14):1370–1380. doi:10.1001/jama.2023.18588 

6. Corcoran CM, Cecchi GA. Using Language Processing and Speech Analysis for the Identification of Psychosis and Other Disorders. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 Aug;5(8):770-779. doi: 10.1016/j.bpsc.2020.06.004. Epub 2020 Jun 14. PMID: 32771179; PMCID: PMC7430500. 

7. Yu-Ching Tseng, Esther Ching-lan Lin, Chung Hsien Wu, Huei-Lin Huang, Po See Chen, Associations among smartphone app-based measurements of mood, sleep and activity in bipolar disorder, Psychiatry Research, Volume 310, 2022, 114425, ISSN 0165-1781, https://doi.org/10.1016/j.psychres.2022.114425. 

8. Busk, J., Faurholt-Jepsen, M., Frost, M. et al. Daily estimates of clinical severity of symptoms in bipolar disorder from smartphone-based self-assessments. Transl Psychiatry 10, 194 (2020). https://doi.org/10.1038/s41398-020-00867-6