Wearable Sensing
Multi-modal Exercises Dataset is a multi- sensor, multi-modal dataset, implemented to benchmark Human Activity Recognition(HAR) and Multi-modal Fusion algorithms. Collection of this dataset was inspired by the need for recognising and evaluating quality of exercise performance to support patients with Musculoskeletal Disorders(MSD).The MEx Dataset contains data from 25 people recorded with four sensors, 2 accelerometers, a pressure mat and a depth camera.
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A new wearable sensing system of respiration rate based on a piezoresistive FlexiForce sensor has been developed. The 3D casing of the system has been designed and printed with a 3D printer. The design of the casing has a direct impact on sensor accuracy. The casing was designed to house all elements of the sensing system in a compact way: microcontroller, battery, conditioning circuit, Bluetooth module and battery charger. The sensing system was validated with twenty-one subjects using a metronome as a reference.
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1608 Views
The data is obtained from electrocardiography, using flexible electrode, Ag/AgCl electrode and Metal Clamp electrode of a femal subject, age 22 years old.
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812 Views
The files contain the research data. The noisy unprocessed audio data and processed audio data using the proposed speech enhancement method are uploaded.
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495 Views
A human-user study with ten healthy subjects provides this experimental setup. The experimental protocol consists in capturing kinematic data while subjects walk, with the donned H2 lower-limb exoskeleton, across seven experimental conditions: Subjects completed 7 trials each. There were 7 different trials, 3 with marks every 30, 45 and 60 cm on 3 separate 10 meter lanes.
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517 Views
In robotic grasping and manipulation, force feedback is one of the most important factors. In the absence of force feedback, force control and compliant grasping is almost impossible. In this study a novel Vibrational Haptic feedback system is designed. The system gives individual digit awareness of a multipronged robotic gripper to the user. It also gives force level feedback from each fingertip and simultaneous multiple force level feedback, all through one wearable elastic “Vibrational Haptic Band (Vi-HaB)”.
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237 Views
AoT for Smart Society provides solutions of industry 4.0 standards in which contains custom-built multisensory wearable suit with cloud connectivity interfaced Artificial Intelligent techniques and Machine Learning algorithms in order to detect, to monitor and to analyze biofeedback control and visualization during human daily activities.
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321 Views
The dataset comprises motion sensor data of 19 daily and sports activities each performed by 8 subjects in their own style for 5 minutes. Five Xsens MTx units are used on the torso, arms, and legs.
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1670 Views
Reference: Laschowski B, McNally W, McPhee J, and Wong A. (2019). Preliminary Design of an Environment Recognition System for Controlling Robotic Lower-Limb Prostheses and Exoskeletons. IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 868-873. DOI: 10.1109/ICORR.2019.8779540.
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619 Views