Hand Movement Audio Message-Based Accelerometer for Paralytic and Disabled Persons
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Individuals with paralysis or severe physical disabilities often face significant barriers in communicating their needs, which can limit their independence and quality of care. This study presents a novel system that translates hand movements into corresponding audio messages and displays them on an LCD, enabling effective communication between patients and caregivers. The device incorporates a 3-axis accelerometer and a microcontroller that processes directional hand gestures to generate preprogrammed messages. Testing demonstrates that the system reliably interprets four primary gestures corresponding to the messages: “I am hungry,” “I want to go to the bathroom,” “I want to watch television,” and “I want to go out.” The device operates effectively for users with partial mobility and accommodates those with speech impairments. Maximum speaker volume is 60 dB, with an operational range of approximately 2 meters. The system provides a practical and low-cost assistive technology solution that may improve patient autonomy, caregiver responsiveness, and quality of life.
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Atallah, L., Lo, B., King, R., & Yang, G. Z. (2012). Validation of an ear-worn accelerometer for gait monitoring. Journal of Biomechanics, 45(10), 1764–1770.
Baraka, A., Loconsole, C., & Rissanen, A. (2019). Human locomotion monitoring using forearm sEMG and accelerometers. IEEE Sensors Journal, 19(18), 7862–7873.
Ghazal, M., Al-Maadeed, S., & Faraj, A. (2015). Fall detection using an ANN with a smartwatch accelerometer and gyroscope. Procedia Computer Science, 60, 215–222.
H. Liu, Z., Wang, Q., & Chen, D. (2018). High-precision vacuum accelerometer for harsh environments. Sensors and Actuators A: Physical, 278, 12–22.
Kristoffersson, A., & Lindén, B. (2020). Wearable sensor systems for gait monitoring in real-life conditions: A systematic review. Journal of Biomedical Informatics, 104, 103390.
Manadhar, S., et al. (2019). Hand gesture vocalizer for the dumb and deaf people using accelerometers. Procedia Computer Science, 152, 68–75.
Mohammed, Z., et al. (2019). Semi-autonomous head motion wheelchair for disabled persons. Biomedical Engineering Letters, 9(4), 387–396.
Nowshin, N., et al. (2018). Infrared sensor-controlled wheelchair for physically disabled people. International Journal of Engineering Science and Technology, 10(5), 65–74.
Pande, V. V., et al. (2014). Hand gesture-based wheelchair movement control for disabled persons using MEMS. Procedia Computer Science, 132, 127–134.
Rajkhanna, U., Mathankumar, M., & Gunasekaran, K. (2014). Hand gesture-based mobile robot control using PIC microcontroller. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(2), 1223–1230.
Tez, S., & Akin, T. (2013). Sandwich three-axis bulk-micromachined accelerometer with multiplexed readout. IEEE Sensors Journal, 13(6), 2102–2111.
Tsai, M. H., et al. (2015). Compact three-axis accelerometer using gap-change comb fingers. Microsystem Technologies, 21, 1457–1468.
Srivastava, P., Chatterjee, S., & Thakur, R. (2018). Gesture-controlled wheelchair using accelerometer IC MMA7361L. Procedia Computer Science, 132, 140–147.

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