Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Liberating Technologies, Inc. (LTI), Holliston, MA 01746, USA.
Sensors (Basel). 2023 Feb 23;23(5):2465. doi: 10.3390/s23052465.
Wireless wearable sensor systems for biomedical signal acquisition have developed rapidly in recent years. Multiple sensors are often deployed for monitoring common bioelectric signals, such as EEG (electroencephalogram), ECG (electrocardiogram), and EMG (electromyogram). Compared with ZigBee and low-power Wi-Fi, Bluetooth Low Energy (BLE) can be a more suitable wireless protocol for such systems. However, current time synchronization methods for BLE multi-channel systems, via either BLE beacon transmissions or additional hardware, cannot satisfy the requirements of high throughput with low latency, transferability between commercial devices, and low energy consumption. We developed a time synchronization and simple data alignment (SDA) algorithm, which was implemented in the BLE application layer without the need for additional hardware. We further developed a linear interpolation data alignment (LIDA) algorithm to improve upon SDA. We tested our algorithms using sinusoidal input signals at different frequencies (10 to 210 Hz in increments of 20 Hz-frequencies spanning much of the relevant range of EEG, ECG, and EMG signals) on Texas Instruments (TI) CC26XX family devices, with two peripheral nodes communicating with one central node. The analysis was performed offline. The lowest average (±standard deviation) absolute time alignment error between the two peripheral nodes achieved by the SDA algorithm was 384.3 ± 386.5 μs, while that of the LIDA algorithm was 189.9 ± 204.7 μs. For all sinusoidal frequencies tested, the performance of LIDA was always statistically better than that of SDA. These average alignment errors were quite low-well below one sample period for commonly acquired bioelectric signals.
近年来，用于生物医学信号采集的无线可穿戴传感器系统发展迅速。通常会部署多个传感器来监测常见的生物电信号，如脑电图（EEG）、心电图（ECG）和肌电图（EMG）。与 ZigBee 和低功耗 Wi-Fi 相比，蓝牙低能耗（BLE）可能是更适合此类系统的无线协议。然而，当前 BLE 多通道系统的时间同步方法，无论是通过 BLE 信标传输还是额外的硬件，都无法满足低延迟、高吞吐量、商业设备之间的可移植性和低能耗的要求。我们开发了一种时间同步和简单数据对齐（SDA）算法，该算法在 BLE 应用层实现，无需额外的硬件。我们进一步开发了一种线性插值数据对齐（LIDA）算法来改进 SDA。我们使用不同频率（10 到 210 Hz，每隔 20 Hz 递增-频率涵盖了 EEG、ECG 和 EMG 信号的大部分相关范围）的正弦输入信号在德州仪器（TI）CC26XX 系列设备上对我们的算法进行了测试，两个外围节点与一个中央节点进行通信。分析是离线进行的。SDA 算法实现的两个外围节点之间的平均（±标准偏差）绝对时间对齐误差最低为 384.3 ± 386.5 μs，而 LIDA 算法的为 189.9 ± 204.7 μs。对于所有测试的正弦频率，LIDA 的性能始终优于 SDA。这些平均对齐误差非常低-远低于常见生物电信号的一个采样周期。
