Bergquist Jake, Rupp Lindsay, Zenger Brian, Brundage James, Busatto Anna, MacLeod Rob S
Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA.
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA.
Hearts (Basel). 2021 Dec;2(4):514-542. doi: 10.3390/hearts2040040. Epub 2021 Nov 5.
Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.
体表电位标测(BSPM)是一种评估心脏生物电活动的非侵入性方法,在研究和临床调查的实际应用方面有着丰富的历史。BSPM可全面采集整个胸部的生物电信号,与标准心电图(ECG)相比,能进行更复杂、更广泛的分析。尽管有其优势,但BSPM并非常见的临床工具。然而,BSPM确实是一种有价值的研究工具,也是其他分析模式(如心电图成像,以及最近的机器学习和人工智能)的输入。在本报告中,我们研究了BSPM的当代用途,并对其在临床和研究环境中的未来前景进行了评估。我们评估了BSPM实施的技术现状,并探索了BSPM数据的先进建模和统计分析的现代应用。我们预测,BSPM将继续是一种有价值的研究工具,并将在计算建模方法与人工智能的交叉领域找到临床应用价值。