research-article

ARM cortex M4-based extensible multimodal wearable platform for sensor research and context sensing from motion & sound

Author:

Daniel RoggenAuthors Info & Claims

UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers

Pages 284 - 289

https://doi.org/10.1145/3410530.3414368

Published: 12 September 2020 Publication History

Abstract

We present an extensible sensor research platform suitable for motion- and sound-based activity and context recognition in wearable and ubiquitous computing applications. The 30x30mm platform is extensible through plug-in boards, which makes it well suited to explore novel sensor technologies. Its firmware can acquire 9-axis inertial measurement unit (IMU) data and device orientation in quaternions at up to 565Hz, sound at 16KHz and external analog inputs, without any programming, allowing for use by non-experts.

The data of distinct modalities can be acquired in isolation or simultaneously for multimodal sensing, and can be streamed over Bluetooth or stored locally. The platform has a real-time clock, which enables the acquisition of the data from multiple nodes with a ±10ppm frequency tolerance, without requiring inter-node connectivity. This is useful to collect data from multiple people.

Acquiring multimodal data, the measured power consumption is 222mW when streaming and 67mW when logging to an SD card. With a 165mAh battery, this leads to 2h15mn and 9h of operation, respectively, with a weight of 10.8g (6.75g without battery).

References

[1]

E. Berlin and K. Van Laerhoven. 2012. Detecting Leisure Activities with Dense Motif Discovery. In 14th ACM Int Conf on Ubiquitous Computing. 250--259.

[2]

N. B. Bharatula, M. Stäger, P. Lukowicz, and Tröster. 2005. Power and Size Optimized Multi-Sensor Context Recognition Platform. In Proc. of the 9th IEEE Int Symp on Wearable Computers. 194--195.

Digital Library

[3]

M. Ciliberto, F. J. Ordoñez Morales, H. Gjoreski, D. Roggen, S. Mekki, and S. Valentin. 2017. High reliability Android application for multidevice multimodal mobile data acquisition and annotation. In Proc. ACM Conference on Embedded Networked Sensor Systems. ACM.

[4]

M. Ciliberto and D. Roggen. 2018. Complex human gestures encoding from wearable inertial sensors for activity recognition. In Proc. International Conference on Embedded Wireless Systems and Networks. ACM, 193--194.

[5]

G. Cohn, D. Morris, S. N. Patel, and D. S. Tan. 2012. Humantenna: Using the Body as an Antenna for Real-Time Whole-Body Interaction. In Proc of CHI.

[6]

H. Harms, R. Winkler, J. Schumm, M. Kusserow, and G. Troester. 2010. ETHOS: Miniature orientation sensor for wearable human motion analysis. In IEEE Sensors. 1037--1042.

[7]

M. Lapinski, E. Berkson, T. Gill, M. Reinold, and J Paradiso. 2009. A Distributed Wearable, Wireless Sensor System for Evaluating Professional Baseball Pitchers and Batters. In Proc Int Symp on Wearable Computers. 131--138.

Digital Library

[8]

G. Laput, C. Yang, R. Xiao, A. Sample, and C. Harrison. 2015. EM-Sense: Touch Recognition of Uninstrumented Electrical and Electromechanical Objects. In Proc UIST. ACM, Charlotte, NC, USA.

[9]

S. Madgwick, A. Harrison, and R. Vaidyanathan. 2011. Estimation of IMU and MARG orientation using a gradient descent algorithm. In IEEE Int Conf on Rehabilitation Robotics.

[10]

M. Paulich, M. Schepers, N. Rudigkeit, and G. Bellusci. 2018. Xsens MTw Awinda: Miniature Wireless Inertial-Magnetic Motion Tracker for Highly Accurate 3D Kinematic Applications. Xsens Technologies B.V., Enschede, Neherlands.

[11]

A. Pouryazdan, R. J. Prance, H. Prance, and D. Roggen. 2016. Wearable electric potential sensing: a new modality sensing hair touch and restless leg movement. In Proc. ACM Int Joint Conf on Pervasive and Ubiquitous Computing: Adjunct. 846--850.

[12]

D. Rodríguez-Martín. 2013. A Wearable Inertial Measurement Unit for Long-Term Monitoring in the Dependency Care Area. Sensors 13, 10 (2013), 14079--14104.

[13]

D. Roggen. 2020. BlueSense4 github repository. https://github.com/droggen/BlueSense4. Accessed: 2020-07-29.

[14]

D. Roggen et al. 2010. Collecting complex activity data sets in highly rich networked sensor environments. In 7th IEEE Int. Conf. on Networked Sensing Systems. 233--240.

[15]

D. Roggen, A. Pouryazdan, and M. Ciliberto. 2018. BlueSense - Designing an extensible platform for wearable motion sensing, sensor research and IoT applications. In Proc. International Conference on Embedded Wireless Systems and Networks. ACM, 177--178.

[16]

R. San-Segundo, H. Bluck, J. Moreno-Pimentel, A. Stisen, and M. Gil-Martin. 2018. Robust Human Activity Recognition using smartwatches and smartphones. Engineering Applications of Artificial Intelligence 72 (2018), 190--202.

Digital Library

[17]

Shimmer. 2020. Shimmer 3 IMU Unit. https://www.shimmersensing.com/products/shimmer3-imu-sensor. Accessed: 2020-06-21.

[18]

SparkFun. 2020. SparkFun 9DoF Razor IMU M0. https://www.sparkfun.com/products/14001. Accessed: 2020-06-22.

[19]

M. Stäger, P. Lukowicz, and G. Tröster. 2007. Power and accuracy trade-offs in sound-based context recognition systems. Pervasive and Mobile Computing 3 (2007), 300--327.

Digital Library

[20]

T. Stiefmeier, D. Roggen, G. Ogris, P. Lukowicz, and G. Tröster. 2008. Wearable Activity Tracking in Car Manufacturing. IEEE Pervasive Computing Magazine 7, 2 (2008), 42--50.

Digital Library

[21]

A. T. Vafeas, M. I. Biswas, X. Fafoutis, A. Elsts, I. Craddock, R. Piechocki, and G. Oikonomou. 2020. Wearable Devices for Digital Health: The SPHERE Wearable 3. ACM, Lyon, France, 236--241.

[22]

L. Wang, H. Gjoreski, M. Ciliberto, S. Mekki, S. Valentin, and D. Roggen. 2019. Enabling reproducible research in sensor-based transportation mode recognition with the Sussex-Huawei dataset. IEEE Access 7 (2019), 10870--10891.

[23]

J.A. Ward, P. Lukowicz, G. Tröster, and T. Starner. 2006. Activity recognition of assembly tasks using body-worn microphones and accelerometers. IEEE Trans. Pattern Analysis and Machine Intelligence 28, 10 (2006), 1553--1567.

Digital Library

[24]

x-io Technologies. 2020. NGIMU. https://x-io.co.uk/ngimu. Accessed: 2020-06-21.

[25]

x-io Technologies. 2020. x-IMU. https://x-io.co.uk/x-imu. Accessed: 2020-06-21.

Cited By

Cobden RZeeshan MRoggen DPrance RPouryazdan A(2023)Characterisation of Wearable Electric-Field Communication Link for BAN Multimedia Applications2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)10.1109/PERCOM56429.2023.10099133(262-269)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PERCOM56429.2023.10099133
Ghasemi FLiedtke LJahre M(2023)PES: An Energy and Throughput Model for Energy Harvesting IoT Systems2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)10.1109/ISPASS57527.2023.00011(13-23)Online publication date: Apr-2023
https://doi.org/10.1109/ISPASS57527.2023.00011
Zeeshan MPouryazdan ACobden RWang SPrance RRoggen D(2022)Electric Field Short-range Over-the-air Communication for Wearable and IoT Applications with Off-the-shelf Microcontrollers2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM54355.2022.00044(251-260)Online publication date: Jun-2022
https://doi.org/10.1109/WoWMoM54355.2022.00044
Show More Cited By

Index Terms

ARM cortex M4-based extensible multimodal wearable platform for sensor research and context sensing from motion & sound
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
2. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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Published In

cover image ACM Conferences

UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers

September 2020

732 pages

ISBN:9781450380768

DOI:10.1145/3410530

General Chairs:
Monica Tentori
CICESE, Mexico
,
Nadir Weibel
UC San Diego
,
Kristof Van Laerhoven
University of Siegen, Germany
,
Program Chairs:
Gregory Abowd
Georgia Tech
,
Flora Salim
RMIT, Australia

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 12 September 2020

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UbiComp/ISWC '20

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UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers

September 12 - 17, 2020

Virtual Event, Mexico

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Cobden RZeeshan MRoggen DPrance RPouryazdan A(2023)Characterisation of Wearable Electric-Field Communication Link for BAN Multimedia Applications2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)10.1109/PERCOM56429.2023.10099133(262-269)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PERCOM56429.2023.10099133
Ghasemi FLiedtke LJahre M(2023)PES: An Energy and Throughput Model for Energy Harvesting IoT Systems2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)10.1109/ISPASS57527.2023.00011(13-23)Online publication date: Apr-2023
https://doi.org/10.1109/ISPASS57527.2023.00011
Zeeshan MPouryazdan ACobden RWang SPrance RRoggen D(2022)Electric Field Short-range Over-the-air Communication for Wearable and IoT Applications with Off-the-shelf Microcontrollers2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM54355.2022.00044(251-260)Online publication date: Jun-2022
https://doi.org/10.1109/WoWMoM54355.2022.00044
Roggen DCobden RPouryazdan AZeeshan M(2022)Wearable FPGA Platform for Accelerated DSP and AI Applications2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops53856.2022.9767398(66-69)Online publication date: 21-Mar-2022
https://doi.org/10.1109/PerComWorkshops53856.2022.9767398
Schipor OVatavu R(2022)GearWheels: A Software Tool to Support User Experiments on Gesture Input with Wearable DevicesInternational Journal of Human–Computer Interaction10.1080/10447318.2022.2098907(1-19)Online publication date: 22-Jul-2022
https://doi.org/10.1080/10447318.2022.2098907

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