Glove-Based Hand Gesture Recognition for Diver Communication

We have developed a smart dive glove that recognizes 13 static hand gestures used in diving communication. The smart glove employs five dielectric elastomer sensors to capture finger motion and implements a machine learning classifier in the onboard electronics to recognize gestures. Five basic classification algorithms are trained and assessed: the decision tree, support vector machine (SVM), logistic regression, Gaussian naïve Bayes, and multilayer perceptron. These basic classifiers were selected as they perform well in multiclass classification problems, can be trained using supervised learning, and are model-based algorithms that can be implemented on a microprocessor. The training dataset was collected from 24 participants providing for a range of different hand sizes. After training, the algorithms were evaluated in a dry environment using data collected from ten new participants to test how well they cope with new information. Furthermore, an underwater experiment was conducted to assess any impact of the underwater environment on each algorithm’s classification. The results show all classifiers performed well in a dry environment. The accuracies and F1-scores range between 0.95 and 0.98, where the logistic regressor and SVM have the highest scores for both the accuracy and F1-score (0.98). The underwater results showed that all algorithms work underwater; however, the performance drops when divers must focus on buoyancy control, breathing, and diver trim.

I. Introduction

Recreational scuba divers, who dive in buddy pairs for improved safety, generally exchange information through hand gestures [1] that can include signals for boat direction, general well-being, air supply, interesting or hazardous marine life, swimming direction, and dive planning. For gesture-based communication to work well, several criteria must be met: a clear line of sight, attention of both divers, and a good understanding of the dive plan. Communication can be compromised when gesture sighting is inhibited, such as in murky water, with environmental obstacles, or simply loss of buddy attention. The above-mentioned factors often lead to the complete breakdown of the buddy system through diver separation that can, on its own, substantially increase the likelihood of an emergency.