A wireless IOT system towards gait detection technique using FSR sensor and wearable IOT devices

The recent advancement in gait analysis combines internet of things that provides better observations of person living behavior. The biomechanical model used for elderly and physically challenged persons is related to gait-related parameters, and the accuracy of the existing systems significantly varies according to different person abilities and their challenges. The paper aims to discuss these issues.,Deployment of wearable sensors in gait analysis provides a better solution while tracking the changes of the personal style, and this proposed model uses an electronics system using force sensing resistor and body sensors.,Experimental results provide an average gait recognition of 95 percent compared to the existing neural network-based gait analysis model based on the walking speeds and threshold values.,The sensors are used to monitor and update the predicted values of a person for analysis. Using IoT a communication process is performed in the research work by identifying a physically challenged person even in crowded areas.

[1]  Christos D. Tarantilis,et al.  Resource constrained routing and scheduling: Review and research prospects , 2017, Eur. J. Oper. Res..

[2]  Carolina Ruiz,et al.  Special issue editorial: Wearable sensor signal processing for smart health , 2018 .

[3]  Sandeep K. Sood,et al.  An Energy-Efficient Architecture for the Internet of Things (IoT) , 2017, IEEE Systems Journal.

[4]  Giancarlo Fortino,et al.  Cloud-based Activity-aaService cyber-physical framework for human activity monitoring in mobility , 2017, Future Gener. Comput. Syst..

[5]  Geyong Min,et al.  Advanced internet of things for personalised healthcare systems: A survey , 2017, Pervasive Mob. Comput..

[6]  William Harwin,et al.  Identifying balance impairments in people with Parkinson's disease using video and wearable sensors. , 2018, Gait & posture.

[7]  Matteo Gadaleta,et al.  IDNet: Smartphone-based Gait Recognition with Convolutional Neural Networks , 2016, Pattern Recognit..

[8]  Yingxu Wang,et al.  Kinect Sensor Gesture and Activity Recognition: New Applications for Consumer Cognitive Systems , 2018, IEEE Consumer Electronics Magazine.

[9]  Po Yang,et al.  Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review , 2018, Journal of Biomedical Informatics.

[10]  A Godfrey,et al.  Wearables for independent living in older adults: Gait and falls. , 2017, Maturitas.

[11]  Jesús Vegas,et al.  Open source hardware based sensor platform suitable for human gait identification , 2017, Pervasive Mob. Comput..

[12]  Ying Wah Teh,et al.  Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges , 2018, Expert Syst. Appl..

[13]  Jesús Vegas,et al.  Open source platform for collaborative construction of wearable sensor datasets for human motion analysis and an application for gait analysis , 2016, J. Biomed. Informatics.