Real-time activity energy expenditure estimation for embedded ambulatory
                        systems using Sensium™ technologies

Ang, Su-Shin; Wieczorkowski-Rettinger, Ksawery; Hernandez-Silveira, Miguel; Carrara, Sandro; Iniewski, Krzysztof

doi:10.1017/cbo9781139629539.049

Cited by 1 publication

(1 citation statement)

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“…The very-low-frequency band (0.003–0.04 Hz) was not included since short-term records were used. All the frequency domain measures are expressed in milliseconds squared (ms 2 ) [ 1 , 2 , 3 , 13 , 35 ]. For the non-linear HRV analysis, where the unpredictability of the five-minute records is evaluated, scatter plots were created by plotting the current interval against the next interval—Poincaré plot.…”

Section: Methodsmentioning

confidence: 99%

Validation of a Wireless Bluetooth Photoplethysmography Sensor Used on the Earlobe for Monitoring Heart Rate Variability Features during a Stress-Inducing Mental Task in Healthy Individuals

Correia

Dias

Costa

et al. 2020

Sensors

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Heart rate variability (HRV), using electrocardiography (ECG), has gained popularity as a biomarker of the stress response. Alternatives to HRV monitoring, like photoplethysmography (PPG), are being explored as cheaper and unobtrusive non-invasive technologies. We report a new wireless PPG sensor that was tested in detecting changes in HRV, elicited by a mentally stressful task, and to determine if its signal can be used as a surrogate of ECG for HRV analysis. Data were collected simultaneously from volunteers using a PPG and ECG sensor, during a resting and a mentally stressful task. HRV metrics were extracted from these signals and compared to determine the agreement between them and to determine if any changes occurred in the metrics due to the stressful task. For both tasks, a moderate/good agreement was found in the mean interbeat intervals, SDNN, LF, and SD2, and a poor agreement for the pNN50, RMSSD|SD1, and HF metrics. The majority of the tested HRV metrics obtained from the PPG signal showed a significant decrease caused by the mental task. The disagreement found between specific HRV features imposes caution when comparing metrics from different technologies. Nevertheless, the tested sensor was successful at detecting changes in the HRV caused by a mental stressor.

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