A multi-camera and multimodal dataset for posture and gait analysis.

Monitoring gait and posture while using assisting robotic devices is relevant to attain effective assistance and assess the user's progression throughout time. This work presents a multi-camera, multimodal, and detailed dataset involving 14 healthy participants walking with a wheeled robotic walker equipped with a pair of affordable cameras. Depth data were acquired at 30 fps and synchronized with inertial data from Xsens MTw Awinda sensors and kinematic data from the segments of the Xsens biomechanical model, acquired at 60 Hz.

From raw measurements to human pose - a dataset with low-cost and high-end inertial-magnetic sensor data.

Wearable technology is expanding for motion monitoring. However, open challenges still limit its widespread use, especially in low-cost systems. Most solutions are either expensive commercial products or lower performance ad-hoc systems.