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.
Highlights
The hand is a complex system, with many degrees of freedom (DoF), that enables humans to perform a large variety of grasping and manipulation actions required in activities of daily living (ADL), using a wide range of objects
Hand kinematics is being studied for purposes such as characterizing healthy hand movement patterns[1], assessing patients’ abilities[2] or the effect of object design on grasping[3]
In this paper we present the KINE-ADL BE-UJI Dataset[21], which contains a total of 1160 recordings with anatomical angles of both hands while performing feeding and cooking activities using a large variety of products
Summary
The hand is a complex system, with many degrees of freedom (DoF), that enables humans to perform a large variety of grasping and manipulation actions required in activities of daily living (ADL), using a wide range of objects. The dataset consists of a Matlab/GNU Octave data structure (.mat) (provided in .csv format) with kinematic data and data about the subjects recruited (age, gender, laterality, weight, height, hand length, hand width and active range of motion (AROM) measured for each DoF). This .mat file is accompanied by a guide where information regarding the environment, tasks, objects, data acquisition system and file structure is detailed, thereby allowing the classification of information regarding these parameters
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