The pressure sensors are represented by black circles, which are located in the three zones of each foot. For the left foot: S1 and S2 cover the forefoot area. S3, S4, and S5 the midfoot area. S6 and S7 the rearfoot or heel area. Similarly, for the right foot: S8 and S9 represent the forefoot area. S10, S11, S12 the midfoot area. S13 and S14 the heel area. The values of each sensor are read by the analog inputs of an Arduino mega 2560.
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.
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.
The database was created with records of psychosocial risk level colombian teachers school using physiological variables from May 2016 to December 2017 in five municipalities of a metropolitan area of city in Colombia. The application of physiological variables was made to the people who voluntarily participated in the study. The names and personal data were kept by the researcher.
Changes in left ventricular (LV) aggregate cardiomyocyte orientation and deformation underlie cardiac function and dysfunction. As such, in vivo aggregate cardiomyocyte "myofiber" strain has mechanistic significance, but currently there exists no established technique to measure in vivo cardiomyocyte strain.
The present dataset is based on implementing of 3 approaches with respect to the acquisition of driver data. The same one that we propose to use a sensor of concentration of alcohol in the environment (physiological), a sensor that measure the temperature of the defined points on driver’s face (biological) and another one that allows to identify and recognize the thickness of the pupil (visual characteristics).
Videosupplement for the reports [Gradov et al., 2010; Adamovich et al., 2014]. For exaple, see (in open access) article Adamovich E.D. [NON-STANDARD EQUIPMENT FOR NEW BIOACUSTIC METROLOGY] // Biomedical Engineering and Electronics]. - 2017. - Issue 1. - DOI: 10.6084/m9.figshare.4879859 [in Russian] {URL: http://biofbe.esrae.ru/pdf/2017/1/1090.pdf} .
