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Accurate estimation of daily total energy expenditure (EE) is a prerequisite for assisted weight management and assessing certain health conditions. The use of wearable sensors for predicting free-living EE is challenged by consistent sensor placement, user compliance, and estimation methods used. This paper examines whether a single ear-worn accelerometer can be used for EE estimation under free-living conditions. An EE prediction model was first derived and validated in a controlled setting using healthy subjects involving different physical activities. Ten different activities were assessed showing a tenfold cross validation error of 0.24. Furthermore, the EE prediction model shows a mean absolute deviation below 1.2 metabolic equivalent of tasks. The same model was applied to a free-living setting with a different population for further validation. The results were compared against those derived from doubly labeled water. In free-living settings, the predicted daily EE has a correlation of \0.74, p = \0.008, and a MAD of \27\, \kcal/day. These results demonstrate that laboratory-derived prediction models can be used to predict EE under free-living conditions. [ABSTRACT FROM PUBLISHER]

Tracking instruments during surgery is becoming a useful acquisition tool for different applications. This article presents a tracking system to detect and track instruments in endoscopic video using biocompatible colour markers. The system tracks single or multiple instruments in the video. The originality of this method is that it combines continuously adaptive shift algorithm with Kalman-filter for real-time tracking of single and multiple surgical instruments during surgery. Preliminary results show that the proposed method has a real-time performance. Moreover it is robust to partial occlusion and smoke. The system shows high sensitivity and specificity results for blue, green and yellow colours. The achieved sensitivity and specificity results are sufficient to apply the system for real-time registration of surgical workflow in-vivo during surgery. [ABSTRACT FROM AUTHOR]