Evaluation of a Head-Tongue Controller for Power Wheelchair Driving by People With Quadriplegia

Sebkhi, Nordine; Bhavsar, Arpan; Sahadat, Nazmus; Baldwin, J. E.; Walling, Erica; Biniker, Amber; Hoefnagel, Michelle; Tonuzi, Geneva; Osborne, Raine; Anderson, David V.; Inan, Omer T.

doi:10.1109/tbme.2021.3113291

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…This method, while simple, direct, cost-effective, and easy to implement, often suffers from frequent identification errors, necessitating further improvements in accuracy. Aura et al [16] and Nordine et al [17], respectively, designed a neck/head motion control device and a head-tongue controller that translates movements into commands to drive an electric wheelchair. However, the presence of a tongue-tracking system can interfere with user behaviors such as eating, drinking, and speaking, making it less user-friendly.…”

Section: Introductionmentioning

confidence: 99%

Novel Extension Control Instrument for Power Wheelchair Based on Kalman Filter Head Motion Detection

Zhang,

Ying,

Tian

et al. 2024

Actuators

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People with upper limb disabilities or high quadriplegia have extremely high requirements for the maneuverability and functionality of power wheelchairs. Normal wheelchairs cannot meet travel tasks, while smart customized wheelchairs are expensive and cannot be popularized. Therefore, a novel extension control instrument for power wheelchairs with low cost, strong scalability, and convenient usage is proposed, which can realize the control of the wheelchair by sensing a change of head posture. The device is divided into a head motion sensing unit (HMSU) and a wheelchair assistance control unit (WACU). The mapping relationship between the head attitude and the subject’s motion intention is established. The inertial measurement module in the HMSU collects the head attitude data and uses the Kalman filtering method to obtain the accurate Euler angle. The WACU is fixed on the original controller of the wheelchair. The joystick is inserted into the extended control mechanism and controlled, instead of the hand, through a 2-degree-of-freedom servo system combined with the pinion and rack push rod structure, thus controlling the movement of the wheelchair. In proceeding, the system can also detect the distance of objects in the environment in real time through the three-direction (front, left, right) ultrasonic ranging sensors installed on the WACU, with a certain obstacle avoidance function. The prototype experiments prove that the extension control instrument developed in this paper based on the Kalman filter can quickly and accurately identify head motion and accurately control the movement of the wheelchair. It is easy to operate and has strong universality, which presents a new low-cost solution for the travel of patients with disabilities.

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Section: Introductionmentioning

confidence: 99%

Novel Extension Control Instrument for Power Wheelchair Based on Kalman Filter Head Motion Detection

Zhang,

Ying,

Tian

et al. 2024

Actuators

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MagTrack: A Wearable Tongue Motion Tracking System for Silent Speech Interfaces

Cao

Ravi

Sebkhi

et al. 2023

J Speech Lang Hear Res

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Purpose: Current electromagnetic tongue tracking devices are not amenable for daily use and thus not suitable for silent speech interface and other applications. We have recently developed MagTrack, a novel wearable electromagnetic articulograph tongue tracking device. This study aimed to validate MagTrack for potential silent speech interface applications. Method: We conducted two experiments: (a) classification of eight isolated vowels in consonant–vowel–consonant form and (b) continuous silent speech recognition. In these experiments, we used data from healthy adult speakers collected with MagTrack. The performance of vowel classification was measured by accuracies. The continuous silent speech recognition was measured by phoneme error rates. The performance was then compared with results using data collected with commercial electromagnetic articulograph in a prior study. Results: The isolated vowel classification using MagTrack achieved an average accuracy of 89.74% when leveraging all MagTrack signals ( x , y , z coordinates; orientation; and magnetic signals), which outperformed the accuracy using commercial electromagnetic articulograph data (only y , z coordinates) in our previous study. The continuous speech recognition from two subjects using MagTrack achieved phoneme error rates of 73.92% and 66.73%, respectively. The commercial electromagnetic articulograph achieved 64.53% from the same subject (66.73% using MagTrack data). Conclusions: MagTrack showed comparable results with the commercial electromagnetic articulograph when using the same localized information. Adding raw magnetic signals would improve the performance of MagTrack. Our preliminary testing demonstrated the potential for silent speech interface as a lightweight wearable device. This work also lays the foundation to support MagTrack's potential for other applications including visual feedback–based speech therapy and second language learning.

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Pupil Control Intelligent Wheelchair based on MediaPipe

Zhou,

Qiu,

et al. 2023

2023 35th Chinese Control and Decision Conference (CCDC)

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Evaluation of a Head-Tongue Controller for Power Wheelchair Driving by People With Quadriplegia

Cited by 4 publications

References 13 publications

Novel Extension Control Instrument for Power Wheelchair Based on Kalman Filter Head Motion Detection

Novel Extension Control Instrument for Power Wheelchair Based on Kalman Filter Head Motion Detection

MagTrack: A Wearable Tongue Motion Tracking System for Silent Speech Interfaces

Pupil Control Intelligent Wheelchair based on MediaPipe

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