液态金属复合材料实时手势识别器具有卓越的识别速度和准确性,Advanced Science

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液态金属复合材料实时手势识别器具有卓越的识别速度和准确性
Advanced Science ( IF 14.3 ) Pub Date : 2024-01-26 , DOI: 10.1002/advs.202305251
Yi Chen ₁ , Zhe Tao ₁ , Ruizhe Chang ₁ , Yudong Cao ₁ , Guolin Yun ₂ , Weihua Li ₃ , Shiwu Zhang ₁ , Shuaishuai Sun ₁

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对于手部缺失或畸形的患者来说，假手在恢复前臂功能方面发挥着至关重要的作用。手势意图识别系统是假手系统中的关键组件。然而，准确、快速地识别手势意图仍然是现有方法中的一个挑战。这里，提出了一种利用液态金属复合传感器手环的实时运动意图识别系统。传感器手环检测前臂肌肉运动产生的压力信号，以识别手势意图。该系统利用液态金属复合材料卓越的压力敏感性和基于优化识别算法的高效分类器，平均离线和实时识别准确率分别为98.2%和92.04%，平均识别速度为0.364 s。因此，该可穿戴系统显示出卓越的识别速度和准确性的优势。此外，该系统还可应用于电动操作、太空探索、远程医疗等无人场景中的假手主从控制。所提出的系统有望在下一代意向控制假手和机器人方面取得重大进展。

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Liquid Metal Composites-Enabled Real-Time Hand Gesture Recognizer with Superior Recognition Speed and Accuracy

Prosthetic hands play a vital role in restoring forearm functionality for patients who have suffered hand loss or deformity. The hand gesture intention recognition system serves as a critical component within the prosthetic hand system. However, accurately and swiftly identifying hand gesture intentions remains a challenge in existing approaches. Here, a real-time motion intention recognition system utilizing liquid metal composite sensor bracelets is proposed. The sensor bracelet detects pressure signals generated by forearm muscle movements to recognize hand gesture intent. Leveraging the remarkable pressure sensitivity of liquid metal composites and the efficient classifier based on the optimized recognition algorithm, this system achieves an average offline and real-time recognition accuracy of 98.2% and 92.04%, respectively, with an average recognition speed of 0.364 s. Thus, this wearable system shows advantages in superior recognition speed and accuracy. Furthermore, this system finds applications in master-slave control of prosthetic hands in unmanned scenarios, such as electrically powered operations, space exploration, and telemedicine. The proposed system promises significant advances in next-generation intent-controlled prosthetic hands and robots.

更新日期：2024-01-27

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