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、运动表现峰值评估、老年人智能家居健康监测或儿童癫痫检测等。然而，可穿戴设备通常依赖于干式传感器，这种传感器容易受到运动、汗水和/或肌肉收缩等人为因素的严重污染，以及未针对生物信号进行优化的数据传输协议。这种灵敏度可能导致非常嘈杂的信号，进而可能导致假警报，从而阻碍现有和新出现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，我们已经证明了它可以准确地分离信号和噪声成分，从而使我们能够(1)盲目地测量生物信号的噪声水平，或信噪比（SNR），(2)只滤除噪声成分，从而准确地增强有噪声的生物信号，以及(3)只关注数据的信号成分，提取相关参数（也称为特征）。从而产生诸如健康监测、诊断和异常检测等噪声鲁棒性特征。这项技术有可能重新定义依赖于可穿戴设备的应用程序的性能范围，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技术，为我们提供最相关和最具竞争力的市场(s)的关键信息，基于技术提供的确定的竞争优势，而不是现有的工具

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.**