June 2024
Spotlight Summary by Félix Chamberland and Benoit Gosselin
PDMS-embedded wearable FBG sensors for gesture recognition and communication assistance
Revolutionizing rehabilitation and healthcare, wearable sensors allow to precisely measure movement and share data on the internet. This study highlights the transformative potential of embedding fiber Bragg grating (FBG) sensors into polydimethylsiloxane (PDMS) for improving accuracy and performance of long-term monitoring. It offers an innovative alternative to electromyography (EMG) and strain gauge fiber sensor methods for gesture recognition and movement detection [1,2].
To overcome challenges like sensor sensitivity, robustness, and miniaturization, this approach leverages light passing through deformed optical fibers for more localized and sensitive movement detection. Moreover, the FBG sensors inherently exhibit stable long-term reliability, surpassing the performance of most traditional strain gauges or similar fiber sensors [3]. Similar to how High-Density EMG (HD-EMG) have improved traditional EMG for hand gesture recognition [4], experiments using FBG sensors on hands have yielded promising results for post-stroke patients and individuals with disabilities. Additionally, placing FBG sensors on the cheeks has exhibited significant potential for enhancing speech communication assistance.
This work demonstrates the practical application of optical technologies in wearables, paving the way for developing low-cost, highly effective portable devices for motor skills rehabilitation.
References:
1. Moin et al.,“A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition”, Nat. Electron. 4(1), 54-63 (2021).
2. Ozon et al., "Motion Detection and Analysis Using Multimaterial Fiber Sensors", IEEE TCAS-I 70(9), 3522-3533 (2023).
3. Kim et al., “Simple and cost-effective method of highly conductive and elastic carbon nanotube/polydimethylsiloxane composite for wearable electronics”, Sci. Rep. 8(1), 1375 (2018).
4. Chamberland et al., "Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning", IEEE TBioCAS 17(5), 968-984 (2023).
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To overcome challenges like sensor sensitivity, robustness, and miniaturization, this approach leverages light passing through deformed optical fibers for more localized and sensitive movement detection. Moreover, the FBG sensors inherently exhibit stable long-term reliability, surpassing the performance of most traditional strain gauges or similar fiber sensors [3]. Similar to how High-Density EMG (HD-EMG) have improved traditional EMG for hand gesture recognition [4], experiments using FBG sensors on hands have yielded promising results for post-stroke patients and individuals with disabilities. Additionally, placing FBG sensors on the cheeks has exhibited significant potential for enhancing speech communication assistance.
This work demonstrates the practical application of optical technologies in wearables, paving the way for developing low-cost, highly effective portable devices for motor skills rehabilitation.
References:
1. Moin et al.,“A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition”, Nat. Electron. 4(1), 54-63 (2021).
2. Ozon et al., "Motion Detection and Analysis Using Multimaterial Fiber Sensors", IEEE TCAS-I 70(9), 3522-3533 (2023).
3. Kim et al., “Simple and cost-effective method of highly conductive and elastic carbon nanotube/polydimethylsiloxane composite for wearable electronics”, Sci. Rep. 8(1), 1375 (2018).
4. Chamberland et al., "Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning", IEEE TBioCAS 17(5), 968-984 (2023).
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Article Information
PDMS-embedded wearable FBG sensors for gesture recognition and communication assistance
Kun Xiao, Zhuo Wang, Yudong Ye, Chuanxin Teng, and Rui Min
Biomed. Opt. Express 15(3) 1892-1909 (2024) View: HTML | PDF