Human hand kinematic data during feeding and cooking tasks

Abstract

This work presents a database of human hand kinematics containing data collected during the performance of a wide variety of activities of daily living involving feeding and cooking. The data were recorded using CyberGlove instrumented gloves on both hands measuring 18 degrees of freedom on each. A total of 20 subjects participated in each part of the experiment, and the objects and their arrangement were the same across subjects, although they performed the tasks in a natural non-directed way. This dataset contains a total of 1160 continuous calibrated recordings taken at 100 Hz during the performance of the tasks, with filtered signal. Statistical descriptive analyses from these data are presented. This database can be useful for machine learning purposes and prostheses control, as well as for the characterization of healthy human hand kinematics.

A calibrated database of kinematics and EMG of the forearm and hand during activities of daily living

“…A wide variability was noticed when considering how angles change in relation to joints. Joint angles have range values in accordance to active range of motion (AROM) values published in recent works 22,23 . Furthermore, all joint angles have, in general, range values within functional range of motion (FROM) values.…”

“…8. Active range of motion (AROMs) for each joint are marked, according to the literature 22,23 . Four ANOVAs were performed to the mean joint angles of the records, one for each factor (joint, phase, subjects and activities).…”

Modelling force-length-activation relationships of wrist and finger extensor muscles

“…The activities, i.e. from 40° extension to 40° flexion at the wrist [50] and between neutral to 50° flexion for MCP joints [51]. In comparison with ECR, EDC is affected by both wrist and finger posture but was exposed to lesser loss of force capacities among the tested postures (Figure 8).…”

Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics

“…Data from the publicly available KINE-ADL BE-UJI database [ 4 ] were used to evaluate the goodness of the method against new kinematic data. In this case, the database contains the hand kinematics of both hands of 20 healthy subjects, whose mean ± SD age was 38 ± 9.5 years, during the performance of a wide variety of ADLs ( Figure 2 ) related to eating and food preparation.…”

“…The recording of hand kinematics can be carried out using different devices that employ different motion capture technologies [ 1 ]: Electrogoniometers [ 2 ], instrumented gloves [ 3 , 4 , 5 ], optical tracking systems [ 6 , 7 , 8 , 9 ] or inertial sensors that incorporate magnetometers, accelerometers, and gyroscopes [ 10 , 11 , 12 , 13 ]. Electrogoniometers are commonly used in clinical practice to measure the range of motion (RoM) of joints [ 14 ].…”