Thomas L Jones 1 , Emily Heiden 1 , Felicity Mitchell 1 , Carole Fogg 1 , Sharon McCready 1 , Laurence Pearce 2 , Melissa Kapoor 3 , Paul Bassett 4 , Anoop J Chauhan 1 Show Affiliations »
Abstract
BACKGROUND: Vital sign measurements are an integral component of clinical care, but current challenges with the accuracy and timeliness of patient observations can impact appropriate clinical decision making. Advanced technologies using techniques such as photoplethysmography have the potential to automate noncontact physiological monitoring and recording, improving the quality and accessibility of this essential clinical information. OBJECTIVE: In this study, we aim to develop the algorithm used in the Lifelight software application and improve the accuracy of its estimated heart rate, respiratory rate, oxygen saturation, and blood pressure measurements. METHODS: This preliminary study will compare measurements predicted by the Lifelight software with standard of care measurements for an estimated population sample of 2000 inpatients, outpatients, and healthy people attending a large acute hospital. Both training datasets and validation datasets will be analyzed to assess the degree of correspondence between the vital sign measurements predicted by the Lifelight software and the direct physiological measurements taken using standard of care methods. Subgroup analyses will explore how the performance of the algorithm varies with particular patient characteristics, including age, sex, health condition, and medication. RESULTS: Recruitment of participants to this study began in July 2018, and data collection will continue for a planned study period of 12 months. CONCLUSIONS: Digital health technology is a rapidly evolving area for health and social care. Following this initial exploratory study to develop and refine the Lifelight software application, subsequent work will evaluate its performance across a range of health characteristics, and extended validation trials will support its pathway to registration as a medical device. Innovations in health technology such as this may provide valuable opportunities for increasing the efficiency and accessibility of vital sign measurements and improve health care services on a large scale across multiple health and care settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14326. ©Thomas L Jones, Emily Heiden, Felicity Mitchell, Carole Fogg, Sharon McCready, Laurence Pearce, Melissa Kapoor, Paul Bassett, Anoop J Chauhan. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 28.01.2021.
BACKGROUND: Vital sign measurements are an integral component of clinical care, but current challenges with the accuracy and timeliness of patient observations can impact appropriate clinical decision making. Advanced technologies using techniques such as photoplethysmography have the potential to automate noncontact physiological monitoring and recording, improving the quality and accessibility of this essential clinical information. OBJECTIVE: In this study, we aim to develop the algorithm used in the Lifelight software application and improve the accuracy of its estimated heart rate, respiratory rate, oxygen saturation, and blood pressure measurements. METHODS: This preliminary study will compare measurements predicted by the Lifelight software with standard of care measurements for an estimated population sample of 2000 inpatients, outpatients, and healthy people attending a large acute hospital. Both training datasets and validation datasets will be analyzed to assess the degree of correspondence between the vital sign measurements predicted by the Lifelight software and the direct physiological measurements taken using standard of care methods. Subgroup analyses will explore how the performance of the algorithm varies with particular patient characteristics, including age, sex, health condition, and medication. RESULTS: Recruitment of participants to this study began in July 2018, and data collection will continue for a planned study period of 12 months. CONCLUSIONS: Digital health technology is a rapidly evolving area for health and social care. Following this initial exploratory study to develop and refine the Lifelight software application, subsequent work will evaluate its performance across a range of health characteristics, and extended validation trials will support its pathway to registration as a medical device. Innovations in health technology such as this may provide valuable opportunities for increasing the efficiency and accessibility of vital sign measurements and improve health care services on a large scale across multiple health and care settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14326. ©Thomas L Jones, Emily Heiden, Felicity Mitchell, Carole Fogg, Sharon McCready, Laurence Pearce, Melissa Kapoor, Paul Bassett, Anoop J Chauhan. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 28.01.2021.
Entities: Chemical
Disease
Gene
Species
Keywords:
health technology; patient deterioration; remote monitoring; vital signs
Year: 2021
PMID： 33507157 PMCID： PMC7878110 DOI： 10.2196/14326
Source DB: PubMed Journal: JMIR Res Protoc ISSN： 1929-0748