Science

QuantActions focuses on digital phenotyping for neurological and mental health. We are the pioneers of TappigraphyTM - a new measurement mechanism that utilizes day-to-day smartphone usage to gain insights into cognitive status and neurological health. This mechanism allows us to collect the precise timing of smartphone touchscreen interactions - in millisecond resolution.

The collected tap data is associated with a variety of cognitive functions, diseases, and overall brain health indicators - and can contribute significantly to the compilation of neurological and mental health insights. Our scientific foundations are built on core brain processes, such as abnormal neural events, motor functions, memory, circadian cycles, and sleep. All contributing to the development of key neurological health indicators. At the same time, many mental health problems (e.g. chronic stress) also lead to cognitive impairments. These can also be captured by our technology and allow us to help identify people who need support in time. Overall, this enables for a more comprehensive understanding of brain health (both neurological and mental).

Tappigraphy is used in a wide range of academic institutions. Thus far, 20+ studies have been conducted, several of which are featured in peer-reviewed publications and others that are in their respective developmental stage.

List of peer-reviewed publications

Ceolini, E., Ridderinkhof R., Ghosh, A. (2024).Age-related behavioral resilience in smartphone touchscreen interaction dynamics
van Nieuw Amerongen A. R., Meppelink A. M., Ghosh A., Thijs R. D. (2024).Real-world smartphone data can trace the behavioural impact of epilepsy: A case study
Ceolini, E. & Ghosh, A. (2023).Common multi-day rhythms in smartphone behavior
Kock, R., Ceolini, E., Groenewegen, L., Ghosh, A. (2023).Neural processing of goal and non-goal-directed movements on the smartphone
Reichenbacher, T., Aliakbariana, M., Ghosh, A., Fabrikant, S. I. (2022).Tappigraphy: continuous ambulatory assessment and analysis of in-situ map app use behaviour
Ceolini, E., Kock, R., Band, G. P. H., Stoet, G., Ghosh, A. (2022).Temporal clusters of age-related behavioral alterations captured in smartphone touchscreen interactions
Ceolini, E., Brunner, I., Bunschoten, J., Majoie, M.H.J.M., Thijs, R. D., Ghosh, A. (2022).A model of healthy aging based on smartphone interactions reveals advanced behavioral age in neurological disease
Van de Ruit, M. & Ghosh, A. (2022)Can you hear me now? Momentary increase in smartphone usage enhances neural processing of task-irrelevant sound tones
Duckrow, R. B., Ceolini, E., Zaveri, H. P., Brooks, C., & Ghosh, A. (2021).Artificial neural network trained on smartphone behavior can trace epileptiform activity in epilepsy.
Huber, R., & Ghosh, A. (2021).Large cognitive fluctuations surrounding sleep in daily living.
Massar, S.A., Chua, X.Y., Soon, C.S., Ng, A.S., Ong, J.L., Chee, N.I., Lee, T.S., Ghosh, A. and Chee, M.W. (2021).Trait-like nocturnal sleep behavior identified by combining wearable, phone-use, and self-report data.
Westbrook, A., Ghosh, A., van den Bosch, R., Määttä, J. I., Hofmans, L., & Cools, R. (2021).Striatal dopamine synthesis capacity reflects smartphone social activity.
Massar, S. A. A., Ng, A. S. C., Soon, C. S., Ong, J. L., Chua, X. Y., Chee, N. I. Y. N., Lee, T. S., Chee, M. W. L. (2021).Reopening after lockdown: the influence of working-from-home and digital device use on sleep, physical activity, and wellbeing following COVID-19 lockdown and reopening
Pfister, J. P., & Ghosh, A. (2020).Generalized priority-based model for smartphone screen touches.
Borger, J. N., Huber, R., & Ghosh, A. (2019).Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions.
Balerna, M., & Ghosh, A. (2018).The details of past actions on a smartphone touchscreen are reflected by intrinsic sensorimotor dynamics.
Gindrat, A. D., Chytiris, M., Balerna, M., Rouiller, E. M., & Ghosh, A. (2015).Use-dependent cortical processing from fingertips in touchscreen phone users.