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Physical Activity Researcher

Physical Activity Researcher

Science

SurPASS: Automating Device-Based Measurement in Cohort Studies - ProPASS Event - Prof Holtermann & Dr Gupta

SurPASS: Automating Device-Based Measurement in Cohort Studies - ProPASS Event - Prof Holtermann & Dr Gupta

2022-07-13
Download

SurPASS: Automating device-based measurement in cohort study research- Prof Andreas Holtermann & Dr Nidhi Gupta

Audio of the ProPASS' 4th Annual Meeting 27-28 April 2022

---

SurPASS is a sister project to ProPASS. SurPASS aims to develop and evaluate an e-system for measuring daily physical behaviours (physical activity, sedentary behaviours, and sleep) at work and non-work time of working adults.

​

The vision of the SurPASS project is to develop a system for measuring physical behaviours in large adult populations that:

  • accurately measures physical behaviours

  • has low participant burden (e.g. easy to use and high hygiene)

  • has low administrative burden (e.g. cheap in cost, automated analytics, low logistic burden, high data security, low expertise demands)

  • can be used in large-scale surveillances and cohorts

  • ​can be used at national and international levels.

 

The system will consist of:

  • A SENS motion® patch-based tri-axial sensor for long-term monitoring of physical behaviours to be attached to the thigh. Such device can be sent to participants via postal mail and participants can attach the sensor themselves. The device can measure and store data for several weeks, and encrypt and transmit data to a secured server.

  • An app on participants' smartphone to initialise the measurements, provide a user guide, automatically upload data to a secured server, and provide visual feedback on the physical behaviours to the participants after the measurement period.

  • A web application for administrators for registering participants, managing sensors, and viewing and exporting data.

  • A secured server based on SENS motion® technology for automatically

    • importing encrypted data from a sensor (via app), decrypting it and storing it regularly

    • cleaning and analysing sensor data based on previously validated algorithms to identify physical behaviours.

---

Physical Activity Researcher Podcast, ProPASS, and ISPAH collaborate to be able to bring you the events and webinars content in easy-to-consume audio format to your favourite podcast app.

The video recording is now available the Members Area of the ISPAH Website.

view more

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Analyzing Experience Sampling Method (ESM) Data: Methodological Approaches and Techniques _ Next-Gen Research Techniques
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Machine Learning in HRV and ECG Analysis _ Next-Gen Research Techniques
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How to Design an Experience Sampling Method (ESM) Study: Key Considerations and Steps _ Next-Gen Research Techniques
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Highlights / How Do We Measure the Physical Activity in Children with Disabilities? E-book (Pt 2) - Ugne Kari
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Single-Lead ECG: The Next Generation of Simple Heart Monitoring for Research _ Next-Gen Research Techniques
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Saving Lives at 50°C: Cooling Vests in Mecca, MS, and Elderly Care – José Näf (Pt4)
2025-05-12
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