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Remote sensing natural time analysis of heartbeat data by means of a portable photoplethysmography device
International Journal of Remote Sensing ( IF 3.4 ) Pub Date : 2020-12-30 , DOI: 10.1080/2150704x.2020.1847351
G. Baldoumas 1, 2 , D. Peschos 1 , G. Tatsis 2 , V. Christofilakis 2 , S. K. Chronopoulos 2 , P. Kostarakis 2 , P. A. Varotsos 3 , N. V. Sarlis 3 , E. S. Skordas 3 , A. Bechlioulis 4 , L. K. Michalis 4 , K. K. Naka 4
Affiliation  

ABSTRACT Very recent work reported that patients can monitor their heartbeat at home and specify their heart conditions by means of a millimetre wave radar, but there exist serious limitations because the radar sensor is sensitive to significant body motions that cause Doppler frequency shifts. Such limitations do not exist when using a recently constructed portable photoplethysmography (PPG) electronic device, which gives results comparable with a standard electrocardiogram (ECG). Since all portable modern devices such as smart phones tablets etc support Bluetooth communication that allows easy and direct communication with our PPG device, it may give us remote sensing heart related information. Applying natural time analysis to data simultaneously collected with an ECG system and a PPG device and using two complexity measures quantifying the entropy change in natural time under time reversal, a distinction is achieved between healthy (H) individuals and congestive heart failure (CHF) patients. Employing a support vector machine classifier for CHF discrimination to a total of 99 individuals (including 67 CHF), we obtained 97.7% sensitivity. In a follow up study challenging results are obtained since during the subsequent period six individuals died, who remarkably obeyed additional complexity measures that may distinguish sudden cardiac death individuals from CHF.

中文翻译:

利用便携式光电容积描记仪对心跳数据进行遥感自然时间分析

摘要 最近的工作报告说,患者可以在家中监测他们的心跳并通过毫米波雷达指定他们的心脏状况,但存在严重的局限性,因为雷达传感器对导致多普勒频移的显着身体运动敏感。使用最近构建的便携式光电容积描记 (PPG) 电子设备时不存在此类限制,其结果可与标准心电图 (ECG) 相媲美。由于所有便携式现代设备(例如智能手机平板电脑等)都支持蓝牙通信,可以轻松直接地与我们的 PPG 设备通信,因此可以为我们提供遥感心脏相关信息。对使用 ECG 系统和 PPG 设备同时收集的数据应用自然时间分析,并使用两种复杂性度量量化时间反转下自然时间的熵变化,区分健康 (H) 个体和充血性心力衰竭 (CHF) 患者. 采用支持向量机分类器对总共 99 个个体(包括 67 个 CHF)进行 CHF 鉴别,我们获得了 97.7% 的灵敏度。在后续研究中获得了具有挑战性的结果,因为在随后的时期内有 6 个人死亡,他们显着地遵守了额外的复杂性措施,可以区分心脏性猝死患者和 CHF。采用支持向量机分类器对总共 99 个个体(包括 67 个 CHF)进行 CHF 鉴别,我们获得了 97.7% 的灵敏度。在后续研究中获得了具有挑战性的结果,因为在随后的时期内有 6 个人死亡,他们显着地遵守了额外的复杂性措施,可以区分心脏性猝死患者和 CHF。采用支持向量机分类器对总共 99 个个体(包括 67 个 CHF)进行 CHF 鉴别,我们获得了 97.7% 的灵敏度。在后续研究中获得了具有挑战性的结果,因为在随后的时期内有 6 个人死亡,他们显着遵守了额外的复杂性措施,可以将心脏性猝死患者与 CHF 区分开来。
更新日期:2020-12-30
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