Using the smartphone camera to monitor heart rate and rhythm in heart failure patients

Lagido, R. B.; Lobo, Joana; Leite, Sérgio; Sousa, Carla; Ferreira, Liliana; Silva-Cardoso, José

doi:10.1109/bhi.2014.6864425

Cited by 22 publications

(11 citation statements)

References 11 publications

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“…In total, 8 studies studied an adult population [70,73,78,80,82,85,87,91] and 2 an infant population [75,90], and 4 studies did not mention the age of the participants [68,79,88,89]. In 9 studies, the reference instrument was an ECG [68,70,75,78,79,82,85,89,90]; in 4 studies, a pulse oximeter [80,87,88,91]; and in 1 study, both [73]. The duration of the measurement varied between 10 s and 5 min.…”

Section: Resultsmentioning

confidence: 99%

“…A total of 5 studies tried to evoke variations in heart rate [68,73,78,82,91], 2 studies controlled the breathing of the participants during measurement [85,89], 1 paper made measurements in different lighting conditions [87], and 1 paper made measurements during different heart rhythms [90]. Overall, 8 studies studied another outcome besides heart rate, namely heart rate variability parameters [68,78,79], other vital parameters [85,89], and other outcomes [70,82,88].…”

Section: Resultsmentioning

confidence: 99%

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Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis

Ridder¹,

Rompaey²,

Kampen³

et al. 2018

JMIR Cardio

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BackgroundSmartphone ownership is rising at a stunning rate. Moreover, smartphones prove to be suitable for use in health care due to their availability, portability, user-friendliness, relatively low price, wireless connectivity, far-reaching computing capabilities, and comprehensive memory. To measure vital signs, smartphones are often connected to a mobile sensor or a medical device. However, by using the white light-emitting diode as light source and the phone camera as photodetector, a smartphone could be used to perform photoplethysmography (PPG), enabling the assessment of vital signs.ObjectiveThe objective of this meta-analysis was to evaluate the available evidence on the use of smartphone apps to measure heart rate by performing PPG in comparison with a validated method.MethodsPubMed and ISI Web of Knowledge were searched for relevant studies published between January 1, 2009 and December 7, 2016. The reference lists of included studies were hand-searched to find additional eligible studies. Critical Appraisal Skills Programme (CASP) Diagnostic Test Study checklist and some extra items were used for quality assessment. A fixed effects model of the mean difference and a random effects model of Pearson correlation coefficient were applied to pool the outcomes of the studies.ResultsIn total, 14 studies were included. The pooled result showed no significant difference between heart rate measurements with a smartphone and a validated method (mean difference −0.32; 99% CI −1.24 to 0.60; P=.37). In adults, the Pearson correlation coefficient of the relation between heart rate measurement with a smartphone and a validated method was always ≥.90. In children, the results varied depending on measuring point and heart rate. The pooled result showed a strong correlation that was significant (correlation coefficient .951; 95% CI 0.906-0.975; P<.001). The reported limits of agreement showed good agreement between a smartphone and a validated method. There was a moderately strong significant negative correlation between the year of publication of the included studies and the mean difference (r=−.69; P<.001).ConclusionsSmartphone apps measuring heart rate by performing PPG appear to agree with a validated method in an adult population during resting sinus rhythm. In a pediatric population, the use of these apps is currently not validated.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis

Ridder¹,

Rompaey²,

Kampen³

et al. 2018

JMIR Cardio

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“…On the detection of any abnormal heart condition, an alarm is generated to stockholders for medical supervision. Another severe cardiac arrhythmia called Atrial Fibrillation (AF) was detected [77] by analyzing HRV and heart rhythm from PPG signals.…”

Section: Photoplethysmography (Ppg) Analysis Using Smartphonementioning

confidence: 99%

Survey: smartphone-based assessment of cardiovascular diseases using ECG and PPG analysis

Shabaan

Arshid

Yaqub

et al. 2020

BMC Med Inform Decis Mak

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A number of resources, every year, being spent to tackle early detection of cardiac abnormalities which is one of the leading causes of deaths all over the Globe. The challenges for healthcare systems includes early detection, portability and mobility of patients. This paper presents a categorical review of smartphone-based systems that can detect cardiac abnormalities by the analysis of Electrocardiogram (ECG) and Photoplethysmography (PPG) and the limitation and challenges of these system. The ECG based systems can monitor, record and forward signals for analysis and an alarm can be triggered in case of abnormality, however the limitation of smart phone’s processing capabilities, lack of storage and speed of network are major challenges. The systems based on PPG signals are non-invasive and provides mobility and portability. This study aims to critically review the existing systems, their limitation, challenges and possible improvements to serve as a reference for researchers and developers.

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“…Heart rate is a heartbeat rhythm that can be sensed on the surface of the skin at certain places [3]. It is the easiest way to determine a person's heart rate and equal to the frequency of the heartbeat.…”

Section: Introductionmentioning

confidence: 99%

“…Several researchers have conducted studies in counting heart rate by using ECG [4][5]. Lagido et al [3] used a smartphone camera to count it while Guo-cheng and Hong-yang [6] developed the research by using light sensors to detect heart rate and calculate heart rate by using iOS platform. However, these tools are too expensive and cannot be implemented by low-income society.…”

Section: Introductionmentioning

confidence: 99%

Low-cost portable heart rate monitoring based on photoplethysmography and decision tree

Tunggal¹,

Latif²,

Iswanto³

2016

AIP Conference Proceedings

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Abstract. Heart disease is caused by a cardiac function which does not work optimally. This illness can be detected by sensing a pulse that is defined as the rhythm of the heartbeat. Some researchers have conducted a study to determine and monitor heart rate. Researches resulted in very expensive and not portable tools. Therefore, this paper examines portable heart rate monitoring with photoplethysmography method and decision tree algorithm. The photoplethysmography method is an optical technique that is cheap and simple that can be used to detect changes in blood volume in the microvascular network. The method modified on the transmitter and receiver sensors. The decision tree algorithm is used to make decisions for one's pulse form of digital data retrieval heart rate. With the decision tree algorithm obtained a normal heart, Bradycardia, and Tachycardia. The method and algorithm result in a much cheaper tool which can detect heart rate which later is categorized into the normal heart, Bradycardia, or Tachycardia.

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Using the smartphone camera to monitor heart rate and rhythm in heart failure patients

Cited by 22 publications

References 11 publications

Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis

Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis

Survey: smartphone-based assessment of cardiovascular diseases using ECG and PPG analysis

Low-cost portable heart rate monitoring based on photoplethysmography and decision tree

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