AIMC Topic: Gestures

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sEMG-Based Hand Movement Regression by Prediction of Joint Angles With Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work takes a step towards a better biosignal based hand gesture recognition by investigating the strategies for a reliable prediction of hand joint angles. Those strategies are especially important for medical applications in order to achieve e....

Deep Learning-based User Authentication with Surface EMG Images of Hand Gestures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
User authentication is an important security mechanism to prevent unauthorized accesses to systems or devices. In this paper, we propose a new user authentication method based on surface electromyogram (sEMG) images of hand gestures and deep anomaly ...

Spatio-temporal continuous gesture recognition under degraded environments: performance comparison between 3D integral imaging (InIm) and RGB-D sensors.

Optics express
In this paper, we introduce a deep learning-based spatio-temporal continuous human gesture recognition algorithm under degraded conditions using three-dimensional (3D) integral imaging. The proposed system is shown as an efficient continuous human ge...

Wearable on-device deep learning system for hand gesture recognition based on FPGA accelerator.

Mathematical biosciences and engineering : MBE
Gesture recognition is critical in the field of Human-Computer Interaction, especially in healthcare, rehabilitation, sign language translation, etc. Conventionally, the gesture recognition data collected by the inertial measurement unit (IMU) sensor...

iRebot: An Interactive Rehabilitation Robot with Gesture Control.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Physical therapy efficacy relies on patient compliance and motivation. However, the monotony, intensity, and expense of most therapy routines do not promote engagement. Technology-based rehabilitation has the potential to provide engaging and cost-ef...

Regression of Hand Movements from sEMG Data with Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Most wearable human-machine interfaces concerning hand movements only focus on classifying a limited number of hand gestures. With the introduction of deep learning, surface electromyography based hand gesture classification systems improved drastica...

A normalisation approach improves the performance of inter-subject sEMG-based hand gesture recognition with a ConvNet.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recently, the subject-specific surface electromyography (sEMG)-based gesture classification with deep learning algorithms has been widely researched. However, it is not practical to obtain the training data by requiring a user to perform hand gesture...

Human gesture recognition under degraded environments using 3D-integral imaging and deep learning.

Optics express
In this paper, we propose a spatio-temporal human gesture recognition algorithm under degraded conditions using three-dimensional integral imaging and deep learning. The proposed algorithm leverages the advantages of integral imaging with deep learni...

Gesture Classification for a Hand Controller Device Using Neural Networks.

Studies in health technology and informatics
This paper presents a convolutional neural network-based classification of the hand flexion and extension gestures used in wrist recovery after injury. The hand gesture recognition device used in our study is the Leap Motion controller. The Leap Moti...

Enhancing Precision in Gesture Detection for Hand Recovery After Injury Using Leap Motion and Machine Learning.

Studies in health technology and informatics
This paper presents an improved solution for detecting gestures with a better precision using the Leap Motion sensor and Machine Learning support. A neural network is trained to recognize a hand rotation gesture expressing the grade of recovery, with...