Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities
Human–machine interface (HMI) systems are increasingly utilized to develop assistive technologies for individuals with disabilities and older adults. This study proposes two HMI systems using piezoelectric sensors to detect facial muscle activations from eye and tongue movements, and accelerometers...
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| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/10/3037 |
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| author | Charoenporn Bouyam Nannaphat Siribunyaphat Dollaporn Anopas May Thu Yunyong Punsawad |
| author_facet | Charoenporn Bouyam Nannaphat Siribunyaphat Dollaporn Anopas May Thu Yunyong Punsawad |
| author_sort | Charoenporn Bouyam |
| collection | DOAJ |
| description | Human–machine interface (HMI) systems are increasingly utilized to develop assistive technologies for individuals with disabilities and older adults. This study proposes two HMI systems using piezoelectric sensors to detect facial muscle activations from eye and tongue movements, and accelerometers to monitor head movements. This system enables hands-free wheelchair control for those with physical disabilities and speech impairments. A prototype wearable sensing device was also designed and implemented. Four commands can be generated using each sensor to steer the wheelchair. We conducted tests in offline and real-time scenarios to assess efficiency and usability among older volunteers. The head–machine interface achieved greater efficiency than the face–machine interface. The simulated wheelchair control tests showed that the head–machine interface typically required twice the time of joystick control, whereas the face–machine interface took approximately four times longer. Participants noted that the head-mounted wearable device was flexible and comfortable. Both modalities can be used for wheelchair control, especially the head–machine interface for patients retaining head movement. In severe cases, the face–machine interface can be used. Moreover, hybrid control can be employed to satisfy specific requirements. Compared to current commercial devices, the proposed HMIs provide lower costs, easier fabrication, and greater adaptability for real-world applications. We will further verify and improve the proposed devices for controlling a powered wheelchair, ensuring practical usability for people with paralysis and speech impairments. |
| format | Article |
| id | doaj-art-180fcc342bf2432c836c40fd266ae2a5 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-180fcc342bf2432c836c40fd266ae2a52025-08-20T03:47:58ZengMDPI AGSensors1424-82202025-05-012510303710.3390/s25103037Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical DisabilitiesCharoenporn Bouyam0Nannaphat Siribunyaphat1Dollaporn Anopas2May Thu3Yunyong Punsawad4School of Informatics, Walailak University, Nakhon Si Thammarat 80160, ThailandSchool of Informatics, Walailak University, Nakhon Si Thammarat 80160, ThailandBiodesign Innovation Center, Department of Parasitology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, ThailandFaculty of Engineering, Cambodia University of Technology and Science, Phnom Penh 121003, CambodiaSchool of Informatics, Walailak University, Nakhon Si Thammarat 80160, ThailandHuman–machine interface (HMI) systems are increasingly utilized to develop assistive technologies for individuals with disabilities and older adults. This study proposes two HMI systems using piezoelectric sensors to detect facial muscle activations from eye and tongue movements, and accelerometers to monitor head movements. This system enables hands-free wheelchair control for those with physical disabilities and speech impairments. A prototype wearable sensing device was also designed and implemented. Four commands can be generated using each sensor to steer the wheelchair. We conducted tests in offline and real-time scenarios to assess efficiency and usability among older volunteers. The head–machine interface achieved greater efficiency than the face–machine interface. The simulated wheelchair control tests showed that the head–machine interface typically required twice the time of joystick control, whereas the face–machine interface took approximately four times longer. Participants noted that the head-mounted wearable device was flexible and comfortable. Both modalities can be used for wheelchair control, especially the head–machine interface for patients retaining head movement. In severe cases, the face–machine interface can be used. Moreover, hybrid control can be employed to satisfy specific requirements. Compared to current commercial devices, the proposed HMIs provide lower costs, easier fabrication, and greater adaptability for real-world applications. We will further verify and improve the proposed devices for controlling a powered wheelchair, ensuring practical usability for people with paralysis and speech impairments.https://www.mdpi.com/1424-8220/25/10/3037human–machine interfaceface–machine interfacetongue–machine interfacepiezoelectric sensorassistive mobility devicessimulated wheelchair |
| spellingShingle | Charoenporn Bouyam Nannaphat Siribunyaphat Dollaporn Anopas May Thu Yunyong Punsawad Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities Sensors human–machine interface face–machine interface tongue–machine interface piezoelectric sensor assistive mobility devices simulated wheelchair |
| title | Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities |
| title_full | Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities |
| title_fullStr | Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities |
| title_full_unstemmed | Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities |
| title_short | Hands-Free Human–Machine Interfaces Using Piezoelectric Sensors and Accelerometers for Simulated Wheelchair Control in Older Adults and People with Physical Disabilities |
| title_sort | hands free human machine interfaces using piezoelectric sensors and accelerometers for simulated wheelchair control in older adults and people with physical disabilities |
| topic | human–machine interface face–machine interface tongue–machine interface piezoelectric sensor assistive mobility devices simulated wheelchair |
| url | https://www.mdpi.com/1424-8220/25/10/3037 |
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