An Evaluation of Commercial Pedometers for Monitoring Slow Walking Speed Populations.

BACKGROUND: Pedometers are considered desirable devices for monitoring physical activity. Two population groups of interest include patients having undergone surgery in the lower extremities or who are otherwise weakened through disease, medical treatment, or surgery procedures, as well as the slow walking senior population. For these population groups, pedometers must be able to perform reliably and accurately at slow walking speeds. The objectives of this study were to evaluate the step count accuracy of three commercially available pedometers, the Yamax (Tokyo, Japan) Digi-Walker(®) SW-200 (YM), the Omron (Kyoto, Japan) HJ-720 (OM), and the Fitbit (San Francisco, CA) Zip (FB), at slow walking speeds, specifically at 1, 2, and 3 km/h, and to raise awareness of the necessity of focusing research on step-counting devices and algorithms for slow walking populations. MATERIALS AND METHODS: Fourteen participants 29.93 ±4.93 years of age were requested to walk on a treadmill at the three specified speeds, in four trials of 100 steps each. The devices were worn by the participants on the waist belt. The pedometer counts were recorded, and the error percentage was calculated. RESULTS: The error rate of all three evaluated pedometers decreased with the increase of speed: at 1 km/h the error rates varied from 87.11% (YM) to 95.98% (FB), at 2 km/h the error rates varied from 17.27% (FB) to 46.46% (YM), and at 3 km/h the error rates varied from 22.46% (YM) to a slight overcount of 0.70% (FB). CONCLUSIONS: It was observed that all the evaluated devices have high error rates at 1 km/h and mixed error rates at 2 km/h, and at 3 km/h the error rates are the smallest of the three assessed speeds, with the OM and the FB having a slight overcount. These results show that research on pedometers' software and hardware should focus more on accurate step detection at slow walking speeds.

Modelling of interaction between a spatula and a human brain.

This paper describes a method for surgery simulation, or more specifically a learning system of how to use a brain spatula. Improper use of brain spatulas can lead to brain tissue lesions such as tearing of brain tissue and ischemia. The idea is to provide surgeons with a tool which can teach them the correlation between deformation and applied force. The system includes a Finite Element based model of the brain in a Virtual Reality setup with haptic feedback. The physical model links the shape of the deformable model with the associated force. The interaction between the spatula and the brain model is handled by a collision response method which aims at smoothing the discrete haptic feedback. The experimental results are promising even though the used force feedback device is somewhat constraining the realism.

Training brain retraction in a virtual reality environment.

A computer based virtual reality system is presented allowing the user to train skills related to brain retraction. The system is designed and the core training system implemented and tested. The initial test shows promising results.