A Low-Cost Wearable Hand Gesture Detecting System Based on IMU and Convolutional Neural Network.
Annu Int Conf IEEE Eng Med Biol Soc
; 2021: 6999-7002, 2021 11.
Article
en En
| MEDLINE
| ID: mdl-34892714
ABSTRACT
In this paper, a low-cost wearable hand gesture detecting system based on distributed multi-node inertial measurement units (IMUs) and central node microcontroller is presented. It can obtain hand kinematic information and transmit data to the remote processing terminal wirelessly. To have a comprehensive understanding of hand kinematics, a convolutional neural network (CNN) model on the terminal is proposed to recognize and classify gestures and the modified Denavit-Hartenberg notation is used to acquire finger spatial locations. The experiment has not only completed a variety of gesture recognitions, but also captured and displayed the orientation and posture of a single finger. The prototype can be used in various occasions such as hand rehabilitation evaluation and human-computer interaction.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Dispositivos Electrónicos Vestibles
/
Gestos
Tipo de estudio:
Health_economic_evaluation
Límite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2021
Tipo del documento:
Article