Magnol.Ai — an Internet of Medical Things (IoMT) Platform for Digital Health Research
Over the past decade, the integration of digital technologies into clinical trials has fundamentally transformed the ability to monitor patients in real-time through wearable sensors, enabling the rapid capture of clinically relevant signals. This transformation has accelerated the development of medicines by providing faster, more objective measurements of therapeutic effects. Central to this technological shift is the Internet of Medical Things (IoMT) platform, with Magnol.Ai serving as a prime example. Magnol.Ai excels in continuously processing and converting vast amounts of digital data, including wearable sensor signals and electronic Patient-Reported Outcomes (ePROs), into actionable clinical insights for digital biomarker (dBM) research. Beyond its pivotal role in clinical research, Magnol.Ai demonstrates versatility as a scalable, real-time edge computing platform in other domains, such as real-time gait computing. By deploying advanced sensors and algorithms for real-time speed of movement tracking, Magnol.Ai underscores its capacity to support a broad range of applications within IoMT.
Authors
- Guangchen Ruan
- Regan Giesting
- Leah Miller
- Neel Patel (ORCID: https://orcid.org/0009-0002-0101-2321)
- Roy Porter
- Brian E. Winger
- Bo Zhang (ORCID: https://orcid.org/0000-0001-5658-9262)
- Hui Zhang (ORCID: https://orcid.org/0000-0001-7201-3984)
- Wentao Li (ORCID: https://orcid.org/0000-0002-7777-0818)
- Jian Yang (ORCID: https://orcid.org/0000-0003-2001-2474)
- Ming Zhong (ORCID: https://orcid.org/0000-0002-1869-2901)
- Hui Xiao (ORCID: https://orcid.org/0000-0003-1136-5702)
- Roland Hartich
- Andrew Kaczorek
Institutions
- Eli Lilly (United States) (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/bigdata62323.2024.10825104
- Citations
- 1
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.18