Rong-Hao Liang

ACM ISWC 2019: International Symposium on Wearable Computers

InDexMo: Exploring Finger-Worn RFID Motion Tracking for Activity Recognition on Tagged Objects

Rong-Hao Liang1, Shun-Yao Yang2, Bing-Yu Chen2

TU Eindhoven1, National Taiwan University2

ACM Digital Library

Abstract

This work explores and evaluates the designs of finger-worn radio-frequency identification (RFID) motion tracking for activity recognition on tagged objects. We propose an index-finger-worn device that consists of a short-range (~2cm) RFID reader and a pair of two inertial measurement units (IMUs), which are mounted at the locations where an artificial nail and a ring are worn. The short-range RFID reader recognizes the tagged object on finger touch, and then the IMU data are used for activity recognition. Data collected from the user of this device allows for a post-hoc analysis, which informs the activity recognition performance in various RFID+IMU and IMU-only configurations on the same task. The results of a ten-participant user study show that when the objects have similar physical form factors, the hybrid RFID motion tracking significantly outperforms the IMU-only tracking, especially in a larger-number set of objects. In our test, three IMU configurations (i.e., NailOnly, RingOnly, and Nail+Ring) achieved comparable action recognition performances, i.e., ≥90% accuracy, with 500 ms recognition time, though the NailOnly RFID+IMU configuration provided the highest wearability. The practical challenges toward a real-world deployment of a finger-worn RFID motion tracking system are also discussed.

Keywords

activity recognition, RFID, nail-mounted device, finger-worn device, motion tracking

Cite this work (ACM)

Rong-Hao Liang, Shun-Yao Yang, and Bing-Yu Chen. 2019. InDexMo: exploring finger-worn RFID motion tracking for activity recognition on tagged objects. In Proceedings of the 23rd International Symposium on Wearable Computers (ISWC '19). Association for Computing Machinery, New York, NY, USA, 129–134. DOI:https://doi.org/10.1145/3341163.3347724

Cite this work (Bibtex)

@inproceedings{10.1145/3341163.3347724,
author = {Liang, Rong-Hao and Yang, Shun-Yao and Chen, Bing-Yu},
title = {InDexMo: Exploring Finger-Worn RFID Motion Tracking for Activity Recognition on Tagged Objects},
year = {2019},
isbn = {9781450368704},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3341163.3347724},
doi = {10.1145/3341163.3347724},
abstract = {This work explores and evaluates the designs of finger-worn radio-frequency identification (RFID) motion tracking for activity recognition on tagged objects. We propose an index-finger-worn device that consists of a short-range (~2cm) RFID reader and a pair of two inertial measurement units (IMUs), which are mounted at the locations where an artificial nail and a ring are worn. The short-range RFID reader recognizes the tagged object on finger touch, and then the IMU data are used for activity recognition. Data collected from the user of this device allows for a post-hoc analysis, which informs the activity recognition performance in various RFID+IMU and IMU-only configurations on the same task. The results of a ten-participant user study show that when the objects have similar physical form factors, the hybrid RFID motion tracking significantly outperforms the IMU-only tracking, especially in a larger-number set of objects. In our test, three IMU configurations (i.e., NailOnly, RingOnly, and Nail+Ring) achieved comparable action recognition performances, i.e., ≥90% accuracy, with 500 ms recognition time, though the NailOnly RFID+IMU configuration provided the highest wearability. The practical challenges toward a real-world deployment of a finger-worn RFID motion tracking system are also discussed.},
booktitle = {Proceedings of the 23rd International Symposium on Wearable Computers},
pages = {129–134},
numpages = {6},
keywords = {activity recognition, RFID, nail-mounted device, finger-worn device, motion tracking},
location = {London, United Kingdom},
series = {ISWC '19}
}