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Collaborative design for remote monitoring tools

research areas

Activity sensing
Digital health
Health data
Participatory science
Patient experience
Patient-clinician collaboration


2023 - 2024

Utilizing collaborative design methodology, we present this work as a proof of concept for a remote monitoring tool for the activity data of athletes and patients with chronic conditions

This project aims to consistently bring the domain-expert end-users of the DSI-Health community into the tool development process, to ensure that features are built and data is visualized in a way that is effective for their work settings. The tool’s focus is the remote monitoring of the activity data of athletes and patients with chronic conditions

Attend our next workshop!

Register your availability here by Tuesday, August 8th, 19:00


To leverage wearable sensor data (multivariate and time oriented) in a web application that:

  • Facilitates remote consultations with patients, or
    • Remotely monitors patient health, or
    • Remotely monitors athlete health and recovery

Such a data analytics interface has potential to be useful in many clinical areas, and as such, we leverage the great diversity of interests of the members of DSI-Health 


To empower domain-expert users (DSI-Health community members) to engage with their patients’/athletes’ wearables data,
to remotely monitor health and recovery of patients/athletes. Our project progress comes from: 

  • DSI-Health community workshops
  • Focus group findings
  • Artifact validation-testing by usability experts
  • Artifact user-testing by focus group of relevant end-users

Our collaborating domain experts include: specialists in mental health, physical rehabilitation, multiple sclerosis, athletics, long-covid, and clinical implementation researchers 


Through focus groups with our collaborators within DSI-Health, we work to:

  • Design an appropriate interactive application for remote monitoring of athletes and/or of patients
  • Establish the necessary user workflows, tasks, and tool requirements necessary to make remote monitoring tooling capable of supporting clinician needs across the healthcare domain
  • Publish the specifications of such a tool in a top-tier venue within the community (e.g., JAMIA, IEEE VIS, ACM CHI)
  • Open a channel for collaboration with clinical stakeholders that allows for the implementation of such a tool in their specific research domain for in-the-wild validation

Workshop activities

First, we discuss what common experiences with have working with sensing and activity data in a patient care setting

Community building

Each of our in-person workshops always ends in a tasty, social apéro


Workshop followup

Based on our diverse expertises, we then contribute to an online notebook detailing each session’s progress. For example, through a collaborative literature search on remote monitoring

Review some workshop 1 results:

DSI-Health community update (June 4th, 2023), and our online project notebook (for DSI-Health members only)

Future plans:

This project's conclusion would allow for a downstream application to be implemented and deployed into the more specific expertise settings of the community's members. If you have interest in such a collaboration, please reach out to the project organizers!

Background information:

Bernard J, Sessler D, Bannach A, May T, Kohlhammer J. 2015. A visual active learning system for the assessment of patient well-being in prostate cancer research. In Proceedings of the 2015 Workshop on Visual Analytics in Healthcare (VAHC ’15). Association for Computing Machinery, New York, NY, USA, Article 1, 1–8.
Díaz-García, J., et al. (2022) Mental Load and Fatigue Assessment Instruments: A Systematic Review. International Journal of Environmental Research and Public Health 19, DOI: 10.3390/ijerph19010419
Mohr, D. C., Zhang, M., & Schueller, S. M. (2017). Personal sensing: understanding mental health using ubiquitous sensors and machine learning. Annual review of clinical psychology, 13, 23-47.
Seshadri DR, Li RT, Voos JE, Rowbottom JR, Alfes CM, Zorman CA, Drummond CK. Wearable sensors for monitoring the internal and external workload of the athlete. NPJ Digit Med. 2019 Jul 29;2:71. doi: 10.1038/s41746-019-0149-2. PMID: 31372506; PMCID: PMC6662809.


The project is financed by the Digital Society Initiative, UZH