Abstract

We present a motion sensor node to support physiotherapy, based on an Inertial Measurement Unit (IMU). The node has wireless interfaces for both data exchange and charging, and is built based on commodity components. It hence provides an affordable solution with a low threshold to technology adoption. We share the hardware design and explain the calibration and validation procedures. The sensor node has an autonomy of 28 h in operation and a standby time of 8 months. On-device sensor fusion yields static results of on average ° with a drift of 2° per half hour. The final prototype weighs 38 g and measures ø6 cm × cm. The resulting motion sensor node presents an easy to use device for both live monitoring of movements as well as interpreting the data afterward. It opens opportunities to support and follow up treatment in medical cabinets as well as remotely.

Highlights

  • In the last few decades, physiotherapy has expanded from focusing on physical treatment solely with massage and stretching to a broader health context

  • We present an Inertial Measurement Unit (IMU)

  • Comparing the proposed sensor to currently available systems like [2,3], we focus on the raw output data rather than developing software that processes this automatically

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Summary

Introduction

The presented motion sensor node exhibits a low complexity and user-friendly solution that can lower the cost with respect to available systems considerably, while preserving the same functionality. We propose an innovative design, based on low-cost sensors, and the operation of the contactless sensor module, including automated calibration, which is in particular relevant to the targeted applications in e-treatment for physiotherapy. This paper is further organized as follows: Section 2 presents the low-complexity design of the wireless sensor node. It zooms in on the calibration and wireless connectivity, as well as how the sensor node was optimized for low energy.

Low Complexity Design of Wireless Motion Sensor Node
Overview of the hardware: sensor around an Inertial
Comparison between available wireless technologies
Wireless Charging
Optimization for Low Energy
Prototype
Validation with
Validation with Real-Life
12. Illustration of first the first exercise:
Opportunities in Supporting e-Treatment in Physiotherapy
Extension to Multiple Sensor Nodes
Conclusions and Future Work
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