SensorShoe: Mobile Gait Analysis for Parkinson's Disease Patients

We present the design and initial evaluation of a mobile gait analysis system, SensorShoe. The target user group is represented by Parkinson's Disease patients, which need continuous assistance with the physical therapy in their home environment. SensorShoe analyses the gait by using a low-power sensor node equipped with movement sensors. In addition, SensorShoe gives real-time feedback and therapy assistance to the patient, and provides the caregivers an effective remote monitoring and control tool

Validation of distal limb mounted inertial-measurement-unit sensors for stride detection in Warmblood horses at walk and trot

BACKGROUND: Inertial-measurement-unit (IMU)-sensor-based techniques are becoming more popular in horses as a tool for objective locomotor assessment. OBJECTIVES: To describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU-sensors. STUDY DESIGN: Prospective validation study comparing IMU-sensors and motion capture with force plate data. METHODS: Seven Warmblood horses equipped with metacarpal/metatarsal IMU-sensors and reflective markers for motion capture were hand walked and trotted over a force plate. Using four custom-built algorithms hoof-on/off timing over the force plate were calculated for each trial from the IMU data. Accuracy of the computed parameters was calculated as the mean difference in milliseconds between the IMU or motion capture generated data and the data from the force plate, precision as the s.d. of these differences and percentage of error with accuracy of the calculated parameter as a percentage of the force plate stance duration. RESULTS: Accuracy, precision and percentage of error of the best performing IMU algorithm for stance duration at walk were 28.5 ms, 31.6 ms and 3.7% for the forelimbs and -5.5 ms, 20.1 ms and -0.8% for the hindlimbs respectively. At trot the best performing algorithm achieved accuracy, precision and percentage of error of -27.6 ms/8.8 ms/-8.4% for the forelimbs and 6.3 ms/33.5 ms/9.1% for the hind limbs. MAIN LIMITATIONS: The described algorithms have not been assessed on different surfaces. CONCLUSIONS: IMU technology can be used to determine temporal kinematic stride variables at walk and trot justifying its use in gait and performance analysis. However, precision of the method may not be sufficient to detect all possible lameness-related changes. These data seem promising enough to warrant further research to evaluate whether this approach will be useful for appraising the majority of clinically relevant gait changes encountered in practice. This article is protected by copyright. All rights reserved