AI system for high precision recognition of hand gestures

The recognition of human hand gestures by AI systems has been a valuable development over the last decade and has been adopted in high-precision surgical robots, health monitoring equipment and in gaming systems. AI gesture recognition systems that were initially visual-only have been improved upon by integrating inputs from wearable sensors, an approach known as'data fusion'. The wearable sensors recreate the skin's sensing ability, one of which is known as'somatosensory'. However, gesture recognition precision is still hampered by the low quality of data arriving from wearable sensors, typically due to their bulkiness and poor contact with the user, and the effects of visually blocked objects and poor lighting. Further challenges arise from the integration of visual and sensory data as they represent mismatched datasets that must be processed separately and then merged at the end, which is inefficient and leads to slower response times.