the measurement of vital signs by lifelight® software in comparison to the standard of care - multi-site development

Conditions: Respiratory Disorder; Diabetes; Cardiovascular Diseases; Critical Care; Trauma and Emergency Care; Primary Care

Summary: aim: to advance the development and accuracy of the lifelight® app for the measurement of vital signs, therefore developing a non-invasive and easy-to-perform means of measuring vital signs which can be implemented across a wide range of settings, both within hospitals and out in the community. method: lifelight® is a computer program ("app") for measuring vital signs which can be used on smart devices that contain a camera. it is able to measure all of the vital signs by measuring very small changes in skin colour that occur each time the heart beats. this means that it does not need to touch the patient. the investigators believe this could be an effective way of measuring vital signs, especially during the covid-19 pandemic when prevention of cross-contamination between patients is essential. patients are also likely to be reassured by a contactless approach. the app uses data from looking at a person's face to calculate the vital signs. this is possible because there are tiny changes in facial skin that occur each time the heart beats. the investigators believe lifelight® could be an effective way of measuring vital signs. the app is still under development, which means that it is still "learning" the best match between the information it collects from the face and the values of vital signs measured using the standard equipment. the app should become more accurate in calculating the vital signs as it sees more and more information from patients. so far, the app has seen data from inpatients, outpatients, patients attending gp surgeries and healthy people. this has improved its accuracy in measuring vital signs. however, the app needs to see more information so that it can be sufficiently accurate for specific clinical applications such as long-term monitoring of hypertension. to do this, it particularly needs to see information from people with abnormal blood pressures and blood oxygen levels. in order to capture the full range of observations, the app will need to be trialled with some of the most critically ill patients - some of these will not have capacity to consent to participation in the study. it also needs to see more data from people with different skin tones so the investigators can be sure it is accurate for all patients. to do this, the investigators will recruit people who are attending one of two hospitals, either as an inpatient, an outpatient, a friend/relative of a patient, or a member of hospital staff. the exact number will depend on how quickly the app "learns" and how many of the vital signs are outside of the normal range. the investigators will take the participant's vital signs using standard clinical equipment whilst recording a video of their face. the investigators will use most of these measurements and video to teach the app how to become more accurate at measuring vital signs. the investigators will keep the remaining data separate and use it to test how accurate the app is. all of the data will be kept securely. the investigators will also collect feedback from participants and healthcare staff on their experiences using the app and information that allows us to assess whether there are any savings to the healthcare economy through use of this technology.

following informed consent, the study staff member will complete a very brief set of demographic and medical history questions, limited to the presence or absence of medical problems and treatment for them. participants with capacity to consent will be recruited into either sub-protocol 1, 2 or 3 on the basis of which vital signs are expected to be abnormal. participants who lack capacity to consent to take part in the study will be recruited into sub-protocol 4. * sub-protocol 1 participants will have blood pressure, oxygen saturation and heart rate measured. * sub-protocol 2 participants will have respiratory rate and oxygen saturation measured. * sub-protocol 3 participants will have oxygen saturation measured. * sub-protocol 4 participants will have blood pressure, heart rate, respiratory rate and oxygen saturation measured. participants may also be recruited to a sub-protocol on the basis of their skin tone. this is because there are targets within sub-protocols 1, 2 and 3 related to skin tone. not all vital signs are collected in all participants to focus study nurse attention on fewer tasks and to avoid collection of data that is not subsequently used to meet the study objectives. this approach should help to keep all aspects of data collection as high quality as possible and is consistent with the gdpr requirement of data minimisation. for all sub-protocol 1, 2, 3 and 4 participants, the study team will complete a set of pre-measurement observation questions. background luminosity will be measured using a handheld lux meter. the staff member will then prepare for and take the participant's routine observations using standard clinical equipment during the same 60-second period that video is captured of the participant's face using the data collect app. best efforts will be made to adhere to the lifelight® measurement conditions listed in appendix b. these measurements and video capture will be repeated once more in the case of sub-protocols 2 and 3, and twice more in the case of sub-protocols 1 and 4. once measurements are concluded, the study staff member will complete the post-measurement observation questions. in all cases, the cleaning protocol outlined in appendix d will be adhered to after each study session. a selection of sub-protocol 1, 2 and 3 participants will be asked to complete a questionnaire related to vital sign monitoring and their preference of lifelight® or other technologies for measuring vital signs.

Eligibility criteria:
inclusion criteria: * 16 years old or above exclusion criteria: * none

Keywords: vital signs innovation lifelight blood pressure oxygen saturation contactless rppg