Effect of sparsity-aware time–frequency analysis on dynamic hand gesture classification with radar micro-Doppler signatures

Dynamic hand gesture recognition is of great importance in human-computer interaction. In this study, the authors investigate the effect of sparsity-driven time-frequency analysis on hand gesture classification. The time-frequency spectrogram is first obtained by sparsity-driven time-frequency analysis. Then three empirical micro-Doppler features are extracted from the time-frequency spectrogram and a support vector machine is used to classify six kinds of dynamic hand gestures. The experimental results on measured data demonstrate that, compared to traditional time-frequency analysis techniques, sparsity-driven time-frequency analysis provides improved accuracy and robustness in dynamic hand gesture classification

The use and function of gestures in word-finding difficulties in aphasia

Background: Gestures are spontaneous hand and arm movements that are part of everyday communication. The roles of gestures in communication are disputed. Most agree that they augment the information conveyed in speech. More contentiously, some argue that they facilitate speech, particularly when word-finding difficulties (WFD) occur. Exploring gestures in aphasia may further illuminate their role. Aims: This study explored the spontaneous use of gestures in the conversation of participants with aphasia (PWA) and neurologically healthy participants (NHP). It aimed to examine the facilitative role of gesture by determining whether gestures particularly accompanied WFD and whether those difficulties were resolved. Methods & Procedures: Spontaneous conversation data were collected from 20 PWA and 21 NHP. Video samples were analysed for gesture production, speech production, and WFD. Analysis 1 examined whether the production of semantically rich gestures in these conversations was affected by whether the person had aphasia, and/or whether there were difficulties in the accompanying speech. Analysis 2 identified all WFD in the data and examined whether these were more likely to be resolved if accompanied by a gesture, again for both groups of participants. Outcomes & Results: Semantically rich gestures were frequently employed by both groups of participants, but with no effect of group. There was an effect of the accompanying speech, with gestures occurring most commonly alongside resolved WFD. An interaction showed that this was particularly the case for PWA. NHP, on the other hand, employed semantically rich gestures most frequently alongside fluent speech. Analysis 2 showed that WFD were common in both groups of participants. Unsurprisingly, these were more likely to be resolved for NHP than PWA. For both groups, resolution was more likely if a WFD was accompanied by a gesture. Conclusions: These findings shed light on the different functions of gesture within conversation. They highlight the importance of gesture during WFD, both in aphasic and neurologically healthy language, and suggest that gesture may facilitate word retrieval

Towards Developing an Effective Hand Gesture Recognition System for Human Computer Interaction: A Literature Survey

Gesture recognition is a mathematical analysis of movement of body parts (hand / face) done with the help of computing device. It helps computers to understand human body language and build a more powerful link between humans and machines. Many research works are developed in the field of hand gesture recognition. Each works have achieved different recognition accuracies with different hand gesture datasets, however most of the firms are having insufficient insight to develop necessary achievements to meet their development in real time datasets. Under such circumstances, it is very essential to have a complete knowledge of recognition methods of hand gesture recognition, its strength and weakness and the development criteria as well. Lots of reports declare its work to be better but a complete relative analysis is lacking in these works. In this paper, we provide a study of representative techniques for hand gesture recognition, recognition methods and also presented a brief introduction about hand gesture recognition. The main objective of this work is to highlight the position of various recognition techniqueswhich can indirectly help in developing new techniques for solving the issues in the hand gesture recognition systems. Moreover we present a concise description about the hand gesture recognition systems recognition methods and the instructions for future research