Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone

By Christopher G. Scully, Jinseok Lee, Joseph Meyer, A. Gorbach, D. Granquist-Fraser, Y. Mendelson, Ki H. Chon. IEEE Transactions on Biomedical Engineering, 2011

474 citations recorded by the source corpus.

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal. We note that this technology can also be used with recently developed algorithms for detection of atrial fibrillation or blood loss.

Subfields: Biomedical Engineering, Cardiology and Cardiovascular Medicine

View Paper: https://www.semanticscholar.org/paper/1acc82b76cfc33985b8e2ed8e8d36dd13f4f43c8

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In Biomedical Engineering

In Cardiology and Cardiovascular Medicine

Citations in the corpus

Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013, methodology): “PPG [67,72,93] [36,53,88] [36,67,72] [53,88] [36,53,67,72] [88,93]”
Photoplethysmography revisited: from contact to noncontact, from point to imaging (2015, unknown): “later showed that multiple physiological parameters, including SpO2, could be assessed using a cellphone with certain calibrations [67].”
PhaseBeat: Exploiting CSI Phase Data for Vital Sign Monitoring with Commodity WiFi Devices (2017, unknown): “Then, the pixel of the frame is transformed into RGB components, which can detect the PPG signal to estimate the heart rate [20].”
Lab And/Or Field? Measuring Personality Processes and Their Social Consequences (2015, background): “Furthermore, smartphones possess more and more builtin sensors (e.g. accelerometry, barometer, temperature and photoplethysmography via camera sensors, Miller, 2012; Scully et al., 2012) and are increasingly available to complement or substitute stand-alone solutions.”
UbiBreathe: A Ubiquitous non-Invasive WiFi-based Breathing Estimator (2015, methodology): “The camera or sensor records the light absorbed by the ﬁnger tissue, and from that video, each frame is processed by splitting each pixel into RGB components whose values can be used to acquire a PPG signal [14,30,38].”
A Survey on Ambient Intelligence in Health Care (2013, unknown): “In recent years, we also have witnessed the emergence of many smart phone apps that are becoming readily available for physiological status monitoring [6], [7], [8].”
Wearable Sensors for Remote Health Monitoring (2017, background): “Other SpO2 monitoring systems such as forehead mounted se sor [108], electronic patc sensor [109] and phone camera based measurement systems [110] can be found in the literature.”
Wi-Sleep: Contactless Sleep Monitoring via WiFi Signals (2014, background): “Another type of unobtrusive sleep monitoring systems rely on video cameras to monitor sleep via sleep posture patterns and breath patterns [24][9][25][10].”
Human Activity Recognition using Inertial, Physiological and Environmental Sensors: A Comprehensive Survey (2020, background): “ records, has already led to an improvement in the healthcare system. In recent years, many smartphone apps, which are becoming available for physiological status monitoring, have become very popular [65, 120, 159]. With modern improvements in sensor networks research, we are on the path of revoluti”