Department of Digital Medicine, Bielefeld University, Bielefeld, Germany.
Smart Sensors Group, Hamburg Technical University, Hamburg, Germany.
JMIR Res Protoc. 2024 Sep 26;13:e63306. doi: 10.2196/63306.
Modern ballistocardiography (BCG) and seismocardiography (SCG) use acceleration sensors to measure oscillating recoil movements of the body caused by the heartbeat and blood flow, which are transmitted to the body surface. Acceleration artifacts occur through intrinsic sensor roll, pitch, and yaw movements, assessed by the angular velocities of the respective sensor, during measurements that bias the signal interpretation.
This observational study aims to generate hypotheses on the detection and elimination of acceleration artifacts due to the intrinsic rotation of accelerometers and their differentiation from heart-induced sensor accelerations.
Multimodal data from 4 healthy participants (3 male and 1 female) using BCG-SCG and an electrocardiogram will be collected and serve as a basis for signal characterization, model modulation, and location vector derivation under parabolic flight conditions from µg to 1.8g. The data will be obtained during a parabolic flight campaign (3 times 30 parabolas) between September 24 and July 25 (depending on the flight schedule). To detect the described acceleration artifacts, accelerometers and gyroscopes (6-degree-of-freedom sensors) will be used for measuring acceleration and angular velocities attributed to intrinsic sensor rotation. Changes in acceleration and angular velocities will be explored by conducting descriptive data analysis of resting participants sitting upright in varying gravitational states.
A multimodal data set will serve as a basis for research into a noninvasive and gentle method of BCG-SCG with the aid of low-noise and synchronous 3D gyroscopes and 3D acceleration sensors. Hypotheses will be generated related to detecting and eliminating acceleration artifacts due to the intrinsic rotation of accelerometers and gyroscopes (6-degree-of-freedom sensors) and their differentiation from heart-induced sensor accelerations. Data will be collected entirely and exclusively during the parabolic flights, taking place between September 2024 and July 2025. Thus, as of June 2024, no data have been collected yet. The data will be analyzed until December 2025. The results are expected to be published by June 2026.
The study will contribute to understanding artificial acceleration bias to signal readings. It will be a first approach for a detection and elimination method.
Deutsches Register Klinische Studien DRKS00034402; https://drks.de/search/en/trial/DRKS00034402.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/63306.
现代心力描记术（BCG）和地震心动描记术（SCG）使用加速度传感器测量心跳和血流引起的身体振荡回弹运动，这些运动被传递到体表。加速度伪影是通过传感器固有的滚动、俯仰和偏航运动产生的，通过各自传感器的角速度进行评估，这些运动会在测量过程中产生信号解释的偏差。
本观察性研究旨在提出关于检测和消除由于加速度计固有旋转引起的加速度伪影的假设，并对其与心脏引起的传感器加速度进行区分。
将使用 BCG-SCG 和心电图收集 4 名健康参与者（3 名男性和 1 名女性）的多模态数据，作为在抛物线飞行条件下进行信号特征描述、模型调制和位置向量推导的基础，从微重力到 1.8g。数据将在 9 月 24 日至 7 月 25 日（取决于飞行计划）期间的抛物线飞行任务中获得（3 次 30 次抛物线）。为了检测描述的加速度伪影，将使用加速度计和陀螺仪（六自由度传感器）测量归因于传感器固有旋转的加速度和角速度。通过对在不同重力状态下直立坐姿的静止参与者进行描述性数据分析，探索加速度和角速度的变化。
多模态数据集将作为研究借助低噪声和同步 3D 陀螺仪和 3D 加速度传感器进行无创、温和的 BCG-SCG 方法的基础。将生成与检测和消除由于加速度计和陀螺仪（六自由度传感器）固有旋转引起的加速度伪影及其与心脏引起的传感器加速度区分相关的假设。数据将完全且仅在 2024 年 9 月至 2025 年 7 月期间的抛物线飞行中收集。因此，截至 2024 年 6 月，尚未收集任何数据。数据分析将持续到 2025 年 12 月。预计结果将于 2026 年 6 月公布。
该研究将有助于了解人为加速度对信号读数的偏差。这将是一种检测和消除方法的初步尝试。
德国临床试验注册处 DRKS00034402；https://drks.de/search/en/trial/DRKS00034402。
国际注册报告标识符（IRRID）：PRR1-10.2196/63306。
