Vibration induced by human motions features a wide frequency spectrum and spatiotemporal-variable directions. Yet, it is challenging to concurrently expand frequency bandwidth and achieve multidirectional capability for effectively human-induced biomechanical energy harvesting and biometrics sensing. In this paper, we report a piezoelectric–electromagnetic hybrid energy harvester with coupled vibrational stabilization and induced frequency-up rotational mechanisms for omnidirectional and broadband vibration energy harvesting. Experimental studies demonstrate the proposed hybrid energy harvester operates effectively over a wide excitation frequency range from 6.0 to 16.0 Hz with omnidirectional responses. The piezoelectric conversion unit can provide a maximum output power of 0.9 mW and the electromagnetic conversion unit’s maximum output power is 22.7 mW. The hybrid energy harvester satisfies the power requirements of different types of portable electronics and realizes various self-charged sensing electronics that are stimulated by human movement. Various types of human motion signals are detected by piezoelectric and electromagnetic units via machine learning techniques to realize self-powered motion monitoring. Compared with a single type of signal, the identification accuracy of the hybrid device is improved from 85.6% to 100%. The proposed energy harvester for self-powered sensing paves the way to green intelligent life such as health management, environmental monitoring and human-machine interaction.

人体运动引起的振动具有广泛的频谱和时空可变方向。然而，同时扩展频率带宽并实现有效的人体诱导生物力学能量收集和生物识别传感的多向能力具有挑战性。在本文中，我们报告了一种压电-电磁混合能量收集器，该能量收集器具有耦合振动稳定和诱导频率上升旋转机制，用于全向和宽带振动能量收集。实验研究表明，所提出的混合能量收集器可在 6.0 至 16.0 Hz 的宽激励频率范围内有效运行，并具有全向响应。压电转换单元可提供最大输出功率为0。9 mW，电磁转换单元最大输出功率为22.7 mW。混合能量采集器满足不同类型便携式电子产品的电源需求，实现各种受人体运动刺激的自充电传感电子产品。通过机器学习技术，通过压电和电磁单元检测各种类型的人体运动信号，实现自供电运动监测。与单一类型信号相比，混合设备的识别准确率从85.6%提高到100%。所提出的用于自供电传感的能量收集器为健康管理、环境监测和人机交互等绿色智能生活铺平了道路。混合能量采集器满足不同类型便携式电子产品的电源需求，实现各种受人体运动刺激的自充电传感电子产品。通过机器学习技术，通过压电和电磁单元检测各种类型的人体运动信号，实现自供电运动监测。与单一类型信号相比，混合设备的识别准确率从85.6%提高到100%。所提出的用于自供电传感的能量收集器为健康管理、环境监测和人机交互等绿色智能生活铺平了道路。混合能量采集器满足不同类型便携式电子产品的电源需求，实现各种受人体运动刺激的自充电传感电子产品。通过机器学习技术，通过压电和电磁单元检测各种类型的人体运动信号，实现自供电运动监测。与单一类型信号相比，混合设备的识别准确率从85.6%提高到100%。所提出的用于自供电传感的能量收集器为健康管理、环境监测和人机交互等绿色智能生活铺平了道路。通过机器学习技术，通过压电和电磁单元检测各种类型的人体运动信号，实现自供电运动监测。与单一类型信号相比，混合设备的识别准确率从85.6%提高到100%。所提出的用于自供电传感的能量收集器为健康管理、环境监测和人机交互等绿色智能生活铺平了道路。通过机器学习技术，通过压电和电磁单元检测各种类型的人体运动信号，实现自供电运动监测。与单一类型信号相比，混合设备的识别准确率从85.6%提高到100%。所提出的用于自供电传感的能量收集器为健康管理、环境监测和人机交互等绿色智能生活铺平了道路。