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An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles.

González I, Fontecha J, Hervás R, Bravo J - Sensors (Basel) (2015)

Bottom Line: The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases.Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc.The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

View Article: PubMed Central - PubMed

Affiliation: MAmI Research Lab, University of Castilla-La Mancha, Esc. Sup. de Informática, Paseo de la Universidad, 4, 13071 Ciudad Real, Spain. ivan.gdiaz@uclm.es.

ABSTRACT
A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

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Insole hardware prototype. Arrangement of FSR sensors on the insole (a). Final prototype (b). Arduino Fio + 9DOF IMU (GY-80) + 3.7V LiPO batt. + Bluetooth module WLS125E1P (c).
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f2-sensors-15-16589: Insole hardware prototype. Arrangement of FSR sensors on the insole (a). Final prototype (b). Arduino Fio + 9DOF IMU (GY-80) + 3.7V LiPO batt. + Bluetooth module WLS125E1P (c).

Mentions: Figure 2 details the hardware components in each insole. The arrangement of FSRs is illustrated in Figure 2a. Each FSR sensor consists of a conductive polymer, which changes its resistance in a predictable manner following the application of force to its surface. The harder the force, the lower its resistance. When no pressure is applied to the FSR, its resistance will be larger than 1 MΩ. The FSRs used here have a round 0.5″ diameter sensing area (provided by Sparkfun [36]). Four FSR sensors are placed on each insole. The first sensor is located at the hallux (toe); two more sensors are located at the forefoot (first and fifth metatarsals); and one more is located at the heel.


An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles.

González I, Fontecha J, Hervás R, Bravo J - Sensors (Basel) (2015)

Insole hardware prototype. Arrangement of FSR sensors on the insole (a). Final prototype (b). Arduino Fio + 9DOF IMU (GY-80) + 3.7V LiPO batt. + Bluetooth module WLS125E1P (c).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541895&req=5

f2-sensors-15-16589: Insole hardware prototype. Arrangement of FSR sensors on the insole (a). Final prototype (b). Arduino Fio + 9DOF IMU (GY-80) + 3.7V LiPO batt. + Bluetooth module WLS125E1P (c).
Mentions: Figure 2 details the hardware components in each insole. The arrangement of FSRs is illustrated in Figure 2a. Each FSR sensor consists of a conductive polymer, which changes its resistance in a predictable manner following the application of force to its surface. The harder the force, the lower its resistance. When no pressure is applied to the FSR, its resistance will be larger than 1 MΩ. The FSRs used here have a round 0.5″ diameter sensing area (provided by Sparkfun [36]). Four FSR sensors are placed on each insole. The first sensor is located at the hallux (toe); two more sensors are located at the forefoot (first and fifth metatarsals); and one more is located at the heel.

Bottom Line: The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases.Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc.The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

View Article: PubMed Central - PubMed

Affiliation: MAmI Research Lab, University of Castilla-La Mancha, Esc. Sup. de Informática, Paseo de la Universidad, 4, 13071 Ciudad Real, Spain. ivan.gdiaz@uclm.es.

ABSTRACT
A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

Show MeSH
Related in: MedlinePlus