随机网络与类脑计算融合的强化学习理论。重点突破：人工智能与大数据技术在心/脑电疾病的智能分析与穿戴式健康监测设备研发；人体运动感知、行为分析与心理疾病监测技术研究。建立运动感知与行为分析、心/脑电等多智能传感器的智慧健康监测系统与远程诊断支撑平台。
It focuses on the study of fundamental theory and algorithms in human-computer hybrid intelligence, including autonomic learning, parallel distributed deep learning, deep random neural network and reinforce learning. It aims to make some breakthroughs in intelligent diagnosis of EEG/ECG data, development of wearable health monitoring devices, human motion perception analysis, behavioral analysis and psychological monitoring. Some platforms are constructed and used for the study of motion perception and behavior analysis, intelligent health monitoring and remote diagnosis.
智能癫痫辅助诊断平台
The intelligent epilepsy-assisted diagnosis platform
智能癫痫辅助诊断平台是基于脑电、心电、运动姿态等多模态人体生理特征分析、深度学习、特征智能算法的智慧医疗机器，可实现癫痫综合征智能分类与癫痫发作期检测与发作前期预警，获得了国家自然科学基金-浙江两化融合重点项目的资助。
The intelligent epilepsy-assisted diagnosis platform is based on multi-modal human physiological characteristics analysis and deep learning, multi-modal feature intelligence theory and algorithm, such as EEG, ECG, and motion posture, to realize intelligent classification of epileptic syndrome and seizure detection and early warning. It has been supported by the Key Program of National Natural Science Foundation of China.