The number of computers is growing, and wearable computers, such as smartwatches, are becoming more and more popular. Devices around the home, such as WiFi bulbs and intelligent thermostats, are also increasing. However, current technologies limit the ability to interact with these devices.

Gestures have been suggested as an intuitive and simple way to interact and control intelligent devices in different environments. For example, you can use gestures to dim the lights in the living room, or to open or close windows. Hand gesture recognition can be achieved in a variety of ways, but the position of the sensor is a major limitation, often excluding some technologies. However, as smartwatch becomes a leading wearable device, this allows sensors to be placed in the watch to sense the movement of the hand.

The Bristol Interactive team at the University of Bristow suggested that ultrasonic imaging of the forearm could be used to recognize gestures. Ultrasound imaging has been used in medicine, such as pregnancy scans and muscle and tendon movements, which researchers have found may be used as a way to understand hand movement.

The team used image processing algorithms and machine learning to classify muscle motion as gestures. The researchers also conducted a user study to find the best sensor location for the technology.

The team's results show very high recognition accuracy, and it is important that the sensor works well on the wrist, which is ideal because it allows future wearables, such as smartwatches, to combine this ultrasonic technology with sensory gestures.

Jess McIntosh, a doctoral student in the Department of computer Science and the BIG Group, said: "using existing technology, there are many practical problems that prevent the integration of small portable ultrasonic imaging sensors into smartwatches. However, our research has taken the first step. What is the most accurate way to detect gestures in a smartwatch? "

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