Inertial Sensor-Based Sport Activity Advisory System Using Machine Learning Algorithms.

The aim of this study was to develop a physical activity advisory system supporting the correct implementation of sport exercises using inertial sensors and machine learning algorithms. Specifically, three mobile sensors (tags), six stationary anchors and a system-controlling server (gateway) were employed for 15 scenarios of the series of subsequent activities, namely squats, pull-ups and dips. The proposed solution consists of two modules: an activity recognition module (ARM) and a repetition-counting module (RCM).

Motion planning for mobile surgery assistant.

The paper presents a method of motion planning for a mobile manipulator acting as a helper providing the necessary tools or a surgery assistant carrying out pre-planned procedures. Mobility of this system makes it possible to reach the position which will give optimal access to the operating field. The path of the end-effector, determined during operation pre-planning, is defined as a curve parameterised by any scaling parameter, the reference trajectory of a mobile platform is not needed.