Maximilian Kerz
King's College London
8 Papers
22 Citations
Maximilian Kerz is an academic researcher from King's College London. The author has contributed to research in topics: mHealth & Induced pluripotent stem cell. The author has an hindex of 6, co-authored 8 publications. Previous affiliations of Maximilian Kerz include National Institute for Health Research.
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Papers
Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
Faith Matcham,C Barattieri di San Pietro,Viola Bulgari,G de Girolamo,Richard Dobson,Hans Eriksson,Amos Folarin,Josep Maria Haro,Maximilian Kerz,Femke Lamers,Qingqin Li,Nikolay V. Manyakov,David C. Mohr,Inez Myin-Germeys,Vaibhav A. Narayan,Penninx Bwjh,Yatharth Ranjan,Z. Rashid,Aki Rintala,Sara Siddi,Sara Simblett,Til Wykes,Matthew Hotopf,Sonia Difrancesco,Katie M White,Alina Ivan,Ashley Polhemus,Jose Ferrao,Michiel Ringkjøbing-Elema,Francesco Nobilia,Wolfgang Viechtbauer,Sjaak Peelen,Zulqarnain Rashid,Janneke Boere,Nicholas Cummins,Nick Meyer +35 more
TL;DR: The RADAR-MDD study as mentioned in this paper is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona, where participants were asked to wear a wrist-worn activity tracker and download several apps onto their smartphones.
Capturing Rest-Activity Profiles in Schizophrenia Using Wearable and Mobile Technologies: Development, Implementation, Feasibility, and Acceptability of a Remote Monitoring Platform
Nicholas Meyer,Maximilian Kerz,Amos Folarin,Dan W. Joyce,Dan W. Joyce,Richard J. Jackson,Chris Karr,Richard Dobson,James H. MacCabe,James H. MacCabe +9 more
TL;DR: Extended use of wearable and mobile technologies are acceptable to people with schizophrenia living in a community setting, and these technologies may allow predictive, objective markers of clinical status, including early markers of impending relapse.
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Human-Centered Design Strategies for Device Selection in mHealth Programs: Development of a Novel Framework and Case Study.
Ashley Polhemus,Ashley Polhemus,Jan Novák,Jan Novák,Jose Ferrao,Sara Simblett,Marta Radaelli,Patrick Locatelli,Faith Matcham,Faith Matcham,Maximilian Kerz,Janice Weyer,Patrick Burke,Vincy Huang,Marissa F. Dockendorf,Gergely Temesi,Til Wykes,Til Wykes,Giancarlo Comi,Inez Myin-Germeys,Amos Folarin,Amos Folarin,Richard Dobson,Nikolay V. Manyakov,Vaibhav A. Narayan,Matthew Hotopf,Matthew Hotopf +26 more
TL;DR: The RADAR-CNS device selection framework provides a structured yet flexible approach to device selection for health care programs and can be used to systematically approach complex decisions that require teams to consider patient experiences alongside scientific priorities and logistical, technical, or regulatory constraints.
SleepSight: a wearables-based relapse prevention system for schizophrenia
Maximilian Kerz,Amos Folarin,Nicholas Meyer,Mark Begale,James H. MacCabe,Richard Dobson +5 more
- 12 Sep 2016
TL;DR: This study tested feasibility and acceptability of the SleepSight system in 15 participants with a diagnosis of schizophrenia, thereby allowing targeted intervention for relapse prevention.
RADAR-base: A Novel Open Source m-Health Platform
Yatharth Ranjan,Maximilian Kerz,Zulqarnain Rashid,Sebastian Böttcher,Richard Dobson,Amos Folarin +5 more
- 08 Oct 2018
TL;DR: RADAR-base, a modern mHealth data collection platform built around Confluent and Apache Kafka, is used presently in RADAR-CNS study to collect data from patients suffering from Multiples Sclerosis, Depression and Epilepsy.
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