SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network

Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-invasively. We recorded 10 second-300 frame fingertip videos using a smartphone in 75 adults. Red, green, and blue pixel intensities were estimated for each of 100 area blocks in each frame and the patterns across the 300 frames were described. ANN was then used to develop a model using the extracted video features to predict hemoglobin levels. In our study sample, with patients 20-56 years of age, and gold standard hemoglobin levels of 7.6 to 13.5 g/dL., we observed a 0.93 rank order of correlation between model and gold standard hemoglobin levels. Moreover, we identified specific regions of interest in the video images which reduced the required feature space

Using an Audience Response System Smartphone App to Improve Resident Education in the Pediatric Intensive Care Unit.

In the Pediatric Intensive Care Unit (PICU), most teaching occurs during bedside rounds, but technology now provides new opportunities to enhance education. Specifically, smartphone apps allow rapid communication between instructor and student. We hypothesized that using an audience response system (ARS) app can identify resident knowledge gaps, guide teaching, and enhance education in the PICU. Third-year pediatric residents rotating through the PICU participated in ARS-based education or received traditional teaching. Before rounds, experimental subjects completed an ARS quiz using the Socrative app. Concomitantly, the fellow leading rounds predicted quiz performance. Then, discussion points based on the incorrect answers were used to guide instruction. Scores on the pre-rotation test were similar between groups. On the post-rotation examination, ARS participants did not increase their scores more than controls. The fellow's prediction of performance was poor. Residents felt that the method enhanced their education whereas fellows reported that it improved their teaching efficiency. Although there was no measurable increase in knowledge using the ARS app, it may still be a useful tool to rapidly assess learners and help instructors provide learner-centered education

Development and Validation of a Smartphone-Based Near-Infrared Optical Imaging Device to Measure Physiological Changes In-Vivo

Smartphone-based technologies for medical imaging purposes are limited, especially when it involves the measurement of physiological information of the tissues. Herein, a smartphone-based near-infrared (NIR) imaging device was developed to measure physiological changes in tissues across a wide area and without contact. A custom attachment containing multiple multi-wavelength LED light sources (690, 800, and 840 nm; and \u3c4 mW of optical power per LED), source driver, and optical filters and lenses was clipped onto a smartphone that served as the detector during data acquisition. The ability of the device to measure physiological changes was validated via occlusion studies on control subjects. Noise removal techniques using singular value decomposition algorithms effectively removed surface noise and distinctly differentiated the physiological changes in response to occlusion. In the long term, the developed smartphone-based NIR imaging device with capabilities to capture physiological changes will be a great low-cost alternative for clinicians and eventually for patients with chronic ulcers and bed sores, and/or in pre-screening for potential ulcers in diabetic subjects

Development of a smartphone-based optical device to measure hemoglobin concentration changes for remote monitoring of wounds

Telemedicine (TM) can revolutionize the impact of diabetic wound care management, along with tools for remote patient monitoring (RPM). There are no low-cost mobile RPM devices for TM technology to provide comprehensive (visual and physiological) clinical assessments. Here, a novel low-cost smartphone-based optical imaging device has been developed to provide physiological measurements of tissues in terms of hemoglobin concentration maps. The device (SmartPhone Oxygenation Tool—SPOT) constitutes an add-on optical module, a smartphone, and a custom app to automate data acquisition while syncing a multi-wavelength near-infrared light-emitting diode (LED) light source (690, 810, 830 nm). The optimal imaging conditions of the SPOT device were determined from signal-to-noise maps. A standard vascular occlusion test was performed in three control subjects to observe changes in hemoglobin concentration maps between rest, occlusion, and release time points on the dorsal of the hand. Hemoglobin concentration maps were compared with and without applying an image de-noising algorithm, single value decomposition. Statistical analysis demonstrated that the hemoglobin concentrations changed significantly across the three-time stamps. Ongoing efforts are in imaging diabetic foot ulcers using the SPOT device to assess its potential as a smart health device for physiological monitoring of wounds remotely

e-CoVig: a novel mHealth system for remote monitoring of symptoms in COVID-19

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).In 2019, a new virus, SARS-CoV-2, responsible for the COVID-19 disease, was discovered. Asymptomatic and mildly symptomatic patients were forced to quarantine and closely monitor their symptoms and vital signs, most of the time at home. This paper describes e-CoVig, a novel mHealth application, developed as an alternative to the current monitoring paradigm, where the patients are followed up by direct phone contact. The e-CoVig provides a set of functionalities for remote reporting of symptoms, vital signs, and other clinical information to the health services taking care of these patients. The application is designed to register and transmit the heart rate, blood oxygen saturation (SpO2), body temperature, respiration, and cough. The system features a mobile application, a web/cloud platform, and a low-cost specific device to acquire the temperature and SpO2. The architecture of the system is flexible and can be configured for different operation conditions. Current commercial devices, such as oximeters and thermometers, can also be used and read using the optical character recognition (OCR) functionality of the system. The data acquired at the mobile application are sent automatically to the web/cloud application and made available in real-time to the medical staff, enabling the follow-up of several users simultaneously without the need for time consuming phone call interactions. The system was already tested for its feasibility and a preliminary deployment was performed on a nursing home showing promising results.This work was funded by Fundação para a Ciência e Tecnologia (FCT) under the grants e-CoVig—Project 255_596880547, and LARSyS—Project UIDB/50009/2020, by FCT/MCTES through national funds and, when applicable, co-funded EU funds under the grant NICE-HOME—Project UIDB/50008/2020, and by the IT—Instituto de Telecomunicações under grant BI/No. 13—19 May 2020 “AIMHealth”, which is gratefully acknowledged.info:eu-repo/semantics/publishedVersio

An auto-titrating (intelligent) oxygen system in patients with chronic respiratory failure

Long-term oxygen therapy (LTOT) improves survival in patients with chronic obstructive pulmonary disease (COPD) and chronic hypoxaemia with international guidelines recommending LTOT for patients with chronic hypoxaemia secondary to respiratory failure. LTOT is prescribed at a fixed-flow rate aiming to maintain the partial pressure of oxygen ≥8 kilopascals or oxygen saturations (SpO2) >90% at rest. However, many patients on domiciliary LTOT continue to experience episodes of intermittent hypoxia (SpO2 <90%) during rest, exercise, activities of daily living (ADL) and sleep with the potentially harmful consequences of arrhythmias, ischaemic heart disease, transient increases in pulmonary pressures and reduced cerebral oxygenation. The aim of this thesis was to explore whether a novel smartphone based auto-titrating oxygen system (the intelligent oxygen therapy system [iO2Ts]), could reduce intermittent hypoxia by delivering variable flow oxygen to maintain a pre-set SpO2 target during various activities which typically take place over a period of 24 hours. In the first study, the iO2Ts significantly reduced intermittent hypoxia compared to ambulatory oxygen in patients with COPD on LTOT during a 6-minute walk test (6MWT). The second study showed that the iO2Ts is equivalent to ambulatory oxygen in reducing intermittent hypoxia during a 6MWT in patients with interstitial lung disease (a group of patients who rapidly desaturate on exercise). The third study showed that the iO2Ts reduced intermittent hypoxia during ADL in patients on LTOT compared to usual LTOT. In a fourth pilot study, the iO2Ts maintained oxygenation as well as usual LTOT and did not change transcutaneous carbon dioxide levels compared to LTOT during sleep. In summary, this thesis has shown that the iO2Ts can reduced intermittent hypoxia in patients on LTOT during various activities which typically take place over 24 hours. The reduction in intermittent hypoxia could optimise domiciliary and ambulatory oxygen for patients on LTOT.Open Acces

Evaluation of a Behind-the-Ear ECG Device for Smartphone based Integrated Multiple Smart Sensor System in Health Applications

In this paper, we present a wireless Multiple Smart Sensor System (MSSS) in conjunction with a smartphone to enable an unobtrusive monitoring of electrocardiogram (ear-lead ECG) integrated with multiple sensor system which includes core body temperature and blood oxygen saturation (SpO2) for ambulatory patients. The proposed behind-the-ear device makes the system desirable to measure ECG data: technically less complex, physically attached to non-hair regions, hence more suitable for long term use, and user friendly as no need to undress the top garment. The proposed smart sensor device is similar to the hearing aid device and is wirelessly connected to a smartphone for physiological data transmission and displaying. This device not only gives access to the core temperature and ECG from the ear, but also the device can be controlled (removed and reapplied) by the patient at any time, thus increasing the usability of personal healthcare applications. A number of combination ECG electrodes, which are based on the area of the electrode and dry/non-dry nature of the surface of the electrodes are tested at various locations near behind the ear. The best ECG electrode is then chosen based on the Signal-to-Noise Ratio (SNR) of the measured ECG signals. These electrodes showed acceptable SNR ratio of ~20 db, which is comparable with existing tradition ECG electrodes. The developed ECG electrode systems is then integrated with commercially available PPG sensor (Amperor pulse oximeter) and core body temperature sensor (MLX90614) using a specialized micro controller (Arduino UNO) and the results monitored using a newly developed smartphone (android) application

Automated Remote Pulse Oximetry System (ARPOS)

Funding: This research is funded by the School of Computer Science and by St Leonard’s Postgraduate College Doctoral Scholarship, both at the University of St Andrews for Pireh Pirzada’s PhD. Early work was funded by the Digital Health & Care Innovation Centre (DHI).Current methods of measuring heart rate (HR) and oxygen levels (SPO2) require physical contact, are individualised, and for accurate oxygen levels may also require a blood test. No-touch or non-invasive technologies are not currently commercially available for use in healthcare settings. To date, there has been no assessment of a system that measures HR and SPO2 using commercial off-the-shelf camera technology that utilises R, G, B and IR data. Moreover, no formal remote photoplethysmography studies have been done in real life scenarios with participants at home with different demographic characteristics. This novel study addresses all these objectives by developing, optimising, and evaluating a system that measures the HR and SPO2 of 40 participants. HR and SPO2 are determined by measuring the frequencies from different wavelength band regions using FFT and radiometric measurements after pre-processing face regions of interest (forehead, lips, and cheeks) from Colour, IR and Depth data. Detrending, interpolating, hamming, and normalising the signal with FastICA produced the lowest RMSE of 7.8 for HR with the r-correlation value of 0.85 and RMSE 2.3 for SPO2. This novel system could be used in several critical care settings, including in care homes and in hospitals and prompt clinical intervention as required.Publisher PDFPeer reviewe

Hyperspectral system for Imaging of skin chromophores and blood oxygenation

We developed a compact, fast, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. Here, we present results of the system tests on healthy volunteers