Market assessment of biosignal quality measurement, enhancement, and noise-robust feature extraction from wearable devices based on modulation sprectrum processing

低成本可穿戴健康监测设备的进步为许多新的应用打开了大门，包括健身跟踪、压力监测、远程健康监测和疾病检测、巅峰运动成绩评估、老年人的智能家居健康监测或儿童的癫痫检测等等。然而，可穿戴设备通常依赖于干式传感器以及未针对生物信号进行优化的数据传输协议，已知的干式传感器受到例如运动、汗水和/或肌肉收缩伪影的高度污染。这种敏感性可能会导致非常嘈杂的信号，进而可能导致错误警报，从而阻碍现有和新兴的健康应用程序的性能。本发明旨在克服这一限制。更具体地说，本发明提出了一种新的信号处理技术，我们已经证明该技术能够准确地分离信号和噪声分量，从而允许我们(1)盲测生物信号噪声电平或信噪比(SNR)，(2)仅滤除噪声分量，从而准确地增强噪声生物信号，以及(3)通过仅聚焦于数据的信号分量来提取相关参数(也称为特征)，从而产生用于例如健康监测、诊断和异常检测的抗噪特征。这项技术有可能重新定义依赖可穿戴设备的应用程序的性能界限，从健康监测到康复、人机交互和智能家居。市场评估将帮助我们进一步完善这项技术，根据该技术相对于现有工具所提供的已确定的竞争优势，为我们提供有关最相关和最具竞争力的市场(S)的关键信息。**

Advances in low-cost wearable health monitoring devices have opened doors for numerous new applications, including fitness tracking, stress monitoring, remote health monitoring and disease detection, peak athletic performance assessment, smart-home health monitoring of the elderly or epilepsy detection for children, to name a few. Wearable devices, however, typically rely on dry sensors, which are known to be highly contaminated by e.g., movement, sweat, and/or muscle contraction artifacts, as well as data transmission protocols not optimized for biosignals. Such sensitivity can lead to very noisy signals, which in turn, can lead to false alarms, thus hampering the performance of existing and emerging health applications. The present invention aims to overcome this limitation. More specifically, the invention proposes a new signal processing technique which we have shown to accurately separate signal and noise components, thus allowing us to (1) blindly measure the biosignal noise level, or signal-to-noise-ratio (SNR), (2) filter out only the noise components, thus accurately enhancing the noisy biosignal, and (3) by focusing only on the signal components of the data, to extract relevant parameters (also known as features), thus leading to noise-robust features for e.g., health monitoring, diagnosis, and abnormality detection. The technology has the potential of redefining the performance envelope of applications relying on wearables, ranging from health monitoring, to rehabilitation, human-machine interaction, and smart homes. The market assessment will help us further refine the technology by providing us with crucial information about the most relevant and competitive market(s) to pursue, based on the identified competitive advantages that the technology provides over existing tools.**