Remote heart rate monitoring - Assessment of the Facereader rPPg by Noldus

Benedetto, Simone; Caldato, Christian; Greenwood, Darren C.; Bartoli, Nicola; Actis, Paolo

doi:10.1371/journal.pone.0225592

Cited by 27 publications

(22 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Participants' age in all studies ranged from 18 to 89 years old. Ethnicity was reported in 65% of studies, which included participants from all skin colour categories of the Fitzpatrick scale (Table 1) [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. Most studies had a small sample size (≤ 30 participants) and were done in a laboratory setting.…”

Section: Demographics and Characteristics Of Studiesmentioning

confidence: 99%

Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis

Pham

Poorzargar

Nagappa

et al. 2021

J Clin Monit Comput

View full text Add to dashboard Cite

The objective of this systematic review and meta-analysis was to analyze the effectiveness of contactless vital sign monitors that utilize a consumer-friendly camera versus medical grade instruments. A multiple database search was conducted from inception to September 2020. Inclusion criteria were as follows: studies that used a consumer-grade camera (smartphone/ webcam) to examine contactless vital signs in adults; evaluated the non-contact device against a reference medical device; and used the participants' face for measurement. Twenty-six studies were included in the review of which 16 were included in Pearson's correlation and 14 studies were included in the Bland-Altman meta-analysis. Twenty-two studies measured heart rate (HR) (92%), three measured blood pressure (BP) (12%), and respiratory rate (RR) (12%). No study examined blood oxygen saturation (SpO 2 ). Most studies had a small sample size (≤ 30 participants) and were performed in a laboratory setting. Our meta-analysis found that consumer-grade contactless vital sign monitors were accurate in comparison to a medical device in measuring HR. Current contactless monitors have limitations such as motion, poor lighting, and lack of automatic face tracking. Currently available consumer-friendly contactless monitors measure HR accurately compared to standard medical devices. More studies are needed to assess the accuracy of contactless BP and RR monitors. Implementation of contactless vital sign monitors for clinical use will require validation in a larger population, in a clinical setting, and expanded to encompass other vital signs including BP, RR, and SpO 2 .

show abstract

Section: Demographics and Characteristics Of Studiesmentioning

confidence: 99%

Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis

Pham

Poorzargar

Nagappa

et al. 2021

J Clin Monit Comput

View full text Add to dashboard Cite

show abstract

“…This finding corroborates the results of a yet to be published study conducted by the developers of the system testing the current version of FaceReader TM heart rate module. 24 A previous investigation by Benedetto et al 48 led to the conclusion that FaceReader TM overestimated lower heart rates and underestimated higher heart rate measurements. The discrepancy between our study and Benedetto et al's 48 could possibly be due to methodological differences including the method used to capture facial expressions and possibly differences in FaceReader TM versions.…”

Section: Discussionmentioning

confidence: 95%

“… 48 led to the conclusion that FaceReader™ overestimated lower heart rates and underestimated higher heart rate measurements. The discrepancy between our study and Benedetto et al.’s 48 could possibly be due to methodological differences including the method used to capture facial expressions and possibly differences in FaceReader™ versions. Although more research is required, our findings add confidence to FaceReader’s™ ability to evaluate heart rate using video of older adult participants.…”

Section: Discussionmentioning

confidence: 99%

“… 46 , 47 Two published studies have used the rPPG system by FaceReader™. 48 , 49 Benedetto and colleagues 48 found that FaceReader’s™ rPPG system calculated insufficiently accurate measurements for low and high heart rates when assessed against the gold standard electrocardiogram (ECG). Given the paucity of research, further examination and improvement of this system are necessary.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automated vs. manual pain coding and heart rate estimations based on videos of older adults with and without dementia

Castillo

Browne

Hadjistavropoulos

et al. 2020

Journal of Rehabilitation and Assistive Technologies Engineerin

View full text Add to dashboard Cite

Introduction Technological advances have allowed for the estimation of physiological indicators from video data. FaceReader™ is an automated facial analysis software that has been used widely in studies of facial expressions of emotion and was recently updated to allow for the estimation of heart rate (HR) using remote photoplethysmography (rPPG). We investigated FaceReader™-based heart rate and pain expression estimations in older adults in relation to manual coding by experts. Methods Using a video dataset of older adult patients with and without dementia, we assessed the relationship between FaceReader’s™ HR estimations against a well-established Video Magnification (VM) algorithm during baseline and pain conditions. Furthermore, we examined the correspondence between the Facial Action Coding System (FACS)-based pain scores obtained through FaceReader™ and manual coding. Results FaceReader’s™ HR estimations were correlated with VM algorithm in baseline and pain conditions. Non-verbal FaceReader™ pain scores and manual coding were also highly correlated despite discrepancies between the FaceReader™ and manual coding in the absolute value of scores based on pain-related facial action coding of the events preceding and following the pain response. Conclusions Compared to expert manual FACS coding and optimized VM algorithm, FaceReader™ showed good results in estimating HR values and non-verbal pain scores.

show abstract

“…Transdermal optical imaging (TOI) allowing detection of facial blood flow changes with a smartphone camera in combination with advanced machine learning techniques has been shown to be capable of determining BP values 31 . This technology uses state-of-the-art remote PPG 32 with extractions of raw signals and estimation of plethysmography signal (band pass filtering). Using a machine learning-based algorithm from a FDA-cleared BP measurement system, TOI extracts haemoglobin-rich signals that are recombined and linked to represent facial blood flow oscillations.…”

Section: Discussionmentioning

confidence: 99%

Blood pressure measurements with the OptiBP smartphone app validated against reference auscultatory measurements

Schoettker

Degott

Hofmann

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Mobile health diagnostics have been shown to be effective and scalable for chronic disease detection and management. By maximizing the smartphones’ optics and computational power, they could allow assessment of physiological information from the morphology of pulse waves and thus estimate cuffless blood pressure (BP). We trained the parameters of an existing pulse wave analysis algorithm (oBPM), previously validated in anaesthesia on pulse oximeter signals, by collecting optical signals from 51 patients fingertips via a smartphone while simultaneously acquiring BP measurements through an arterial catheter. We then compared smartphone-based measurements obtained on 50 participants in an ambulatory setting via the OptiBP app against simultaneously acquired auscultatory systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean blood pressure (MBP) measurements. Patients were normotensive (70.0% for SBP versus 61.4% for DBP), hypertensive (17.1% vs. 13.6%) or hypotensive (12.9% vs. 25.0%). The difference in BP (mean ± standard deviation) between both methods were within the ISO 81,060–2:2018 standard for SBP (− 0.7 ± 7.7 mmHg), DBP (− 0.4 ± 4.5 mmHg) and MBP (− 0.6 ± 5.2 mmHg). These results demonstrate that BP can be measured with accuracy at the finger using the OptiBP smartphone app. This may become an important tool to detect hypertension in various settings, for example in low-income countries, where the availability of smartphones is high but access to health care is low.

show abstract

Remote heart rate monitoring - Assessment of the Facereader rPPg by Noldus

Cited by 27 publications

References 63 publications

Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis

Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis

Automated vs. manual pain coding and heart rate estimations based on videos of older adults with and without dementia

Blood pressure measurements with the OptiBP smartphone app validated against reference auscultatory measurements

Contact Info

Product

Resources

About