EMUs: Enhanced Monitoring Using Sensors After Surgery (EMUs)

February 6, 2026 updated by: University of Edinburgh

Patients can become critically unwell following surgical operations. Delay in recognition of this deterioration can result in patient harm and even death. Wearable wireless sensors that record patients vital signs such as heart rate could help improve recognition of patient deterioration. The goal of this observational study: Enhanced Monitoring Using Sensors After Surgery (EMUs) is to determine if data from wearable physiological monitors can be used for the early detection of postoperative deterioration, while being acceptable to patients and healthcare staff. The study participants and surgical inpatients undergoing open surgery. There are 3 objectives which each represent a stage of the study:

  1. To perform usability testing of device with clinicians, nurses, and healthcare workers in non-clinical environment.
  2. To determine baseline postoperative monitoring practice across our network and perform device usability testing in clinical environment.
  3. To perform a shadow-mode cohort study with collection of time-stamped sensor clinical event data to determine relationships between physiological waveforms and patient deterioration.

This registration focuses on the shadow-mode cohort study.

Participants will wear wireless sensors on their chest and fingers, pre-, intra-, and post-operatively for up to 10 days. The sensors will record their vital signs such as heart rate, and oxygen levels. This will then be analysed, and used to aid the design of early detection algorithms that may be able to predict clinical illness or complications in this patient group. This is an observational study gathering real time data only. No changes in patient care will result, and in Stages 2 and 3 no sensor data will be available to clinical teams. This study will be performed in departments of general surgery in Benin, Ghana, Guatemala, India, Mexico, Nigeria, Rwanda, and the United Kingdom.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Patients who die after surgery frequently have treatable complications which are not identified in a timely manner. This is due to a failure to "recognize", "relay" or "react" to the deterioration of a patient in the postoperative period. This study aims to determine whether data from wearable physiological monitors can be used for the early detection of patient deterioration, while being acceptable to patients and healthcare staff. If found useful, future studies would be conducted to determine the performance and safety of such a device.

This study has three objectives which will be addressed in three stages.

STAGE 1. Usability testing of device with clinicians, nurses, and healthcare workers in non-clinical environment.

STAGE 2. Baseline postoperative monitoring practice assessment and device usability testing in clinical environment.

STAGE 3. Shadow-mode cohort study with collection of time-stamped sensor and clinical event data to determine relationships between physiological waveforms and patient deterioration.

This registration focuses on the shadow-mode cohort study.

This study will be performed in departments of general surgery in Benin, Ghana, Guatemala, India, Mexico, Nigeria, Rwanda, and the UK. In Stages 2 and 3, patients will have undergone major surgery and will be recovering in postoperative wards.

This study can be performed using any suitable wearable device (it is device agnostic), as it seeks to gather generalisable information. In the first instance, the Sibel ANNE® One device will be used. ANNE® One is a wireless ICU-grade dual sensor system that provides real-time physiological monitoring. The system features two skin-mounted, bio-integrated sensors that provide continuous storage of vital sign measurements and physiological waveforms.

This is an observational study gathering real time data only. No changes in patient care will result, and in Stages 2 and 3 no sensor data will be available to clinical teams. True equipoise exists: it is not clear whether these data are useful or how they should be used. Patients will be managed with standard care throughout.

Wearable sensors have potential application in improving postoperative monitoring and consequently, the reduction of avoidable morbidity and mortality. Sensor data may be used to generate prediction algorithms providing a continuous readout of individual patient risk. Such algorithms could enhance healthcare workers' capacity to identify and intervene upon patients with early complications. However, few high-quality studies have yet been performed in this area.

This study has approvals form the following ethical review boards:

Edinburgh Medical School Research Ethics Committee West of Scotland Research Ethics Service (on behalf of NHS Health Research Authority) Health and Care Research Wales (on behalf of NHS Health Research Authority) Ghana Health Service Ethics Review Committee Comite de Investigacion, Hospital General San Juan de Dios, Guatemala, Guatemala Christian Medical College and Hospital, Institutional Ethics Committee, Ludhiana, India El Comite de Etica en Investigacion del Hospital General de Boca del Rio, Veracruz, Mexico Lagos University Teaching Hospital Health Research Ethics Committee, Lagos Nigeria Lagos State University Teaching Hospital Health Research Ethics Committee, Ikeja, Nigeria Obafemi Awolowo University Hospitals Teaching Complex, Ethics and Research Committee, Ife, Nigeria Ethics Committee of University Teaching Hospital of Kigali, Kigali, Rwanda

Study Type

Observational

Enrollment (Estimated)

1332

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

  • Name: Eilidh Gunn
  • Phone Number: +44 (0)131 651 7869
  • Email: egunn3@ed.ac.uk

Study Locations

  • Benin
    • Atlantique Department
      • Ouidah, Atlantique Department, Benin
    • Borgou Department
      • Parakou, Borgou Department, Benin
        • Recruiting
        • Centre Hospitalier Universitaire Departemental Borgou-Alibori
        • Contact:
    • Littoral Department
      • Cotonou, Littoral Department, Benin
        • Recruiting
        • Centre Hospitalier Universitaire Mere Enfant Lagune
        • Contact:
    • Oeume
      • Porto-Novo, Oeume, Benin
        • Recruiting
        • Centre Hospitalier Universitaire et Departemental Oueme Plateau
        • Contact:
  • Ghana
      • Tamale, Ghana
    • Berekum East
      • Berekum, Berekum East, Ghana
    • Bono East
      • Techiman, Bono East, Ghana
  • Guatemala
      • Guatemala City, Guatemala
        • Recruiting
        • Hospital General San Juan de Dios
        • Contact:
  • India
    • Himachal Pradesh
    • Madhya Pradesh
    • Punjab
      • Ludhiana, Punjab, India
  • Mexico
  • Nigeria
  • Rwanda
      • Kigali, Rwanda
        • Not yet recruiting
        • University Teaching Hospital of Rwanda
        • Contact:
  • United Kingdom
      • Edinburgh, United Kingdom, EH16 4SA
        • Active, not recruiting
        • Royal Infirmary of Edinburgh

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

The study population are all patients undergoing a surgical procedure at the NIHR Global Health Research Unit on Global Surgery hubs/spoke hospitals in India, Nigeria, Ghana, Guatemala, Mexico, Rwanda, Benin and the United Kingdom that fit the eligibility criteria.

Description

Participant Inclusion Criteria:

  • Adults 18 years and older.
  • Undergoing an elective or emergency major surgery procedure with a planned skin incision of 5 cm or greater. Any indication for surgery can exist, including benign, malignant, and trauma.
  • Willing and able to provide written informed consent.

Participant Exclusion Criteria:

  • Those under the age of 18.
  • A documented or suspected allergy to adhesive dressings.
  • Obstetric patients
  • Unwilling or unable to provide written informed consent.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Study Cohort
All surgical patients that fit the study eligibility criteria.
Device: Wearable Wireless Sensor
Stage III is a shadow mode evaluation of the device with participants wearing sensors pre-, intra-, and post-operatively. Sensor and clinical data will be collected contemporaneously in the clinical environment. No sensor data is made available to clinical teams for decision making, with no change in patient care.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Cardiovascular data from wearable device
Time Frame: 0-10 days from device application.
Data includes core vital sign measures to assess the patient's cardiovascular function (e.g. heart rate in beats per minute), advanced indices (e.g., pulse arrival time, Heart Rate (HR) /Respiratory Rate (RR) quotient) and raw waveform data.
0-10 days from device application.
Respiratory data from wearable device
Time Frame: 0-10 days from device application.
Data includes core vital sign measures to assess the patient's respiratory function (e.g. oxygen saturation as a percentage), advanced indices (e.g, Heart Rate (HR) /Respiratory Rate (RR) quotient) and raw waveform data.
0-10 days from device application.
Body temperature data from wearable device
Time Frame: 0-10 days from device application.
Data includes core vital sign measures (e.g. temperature measurement in degrees centigrade), advanced indices, and raw waveform data.
0-10 days from device application.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Standard-of-care cardiovascular vital sign observation data
Time Frame: 0-10 days from day of device application.
Standard-of-care vital sign observation data to assess cardiovascular function e.g. heart rate in beats per minute, blood pressure in mmHg at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration or equivalent in participating centers.
0-10 days from day of device application.
Standard-of-care respiratory vital sign observation data
Time Frame: 0-10 days from day of device application.
Standard-of-care vital sign observation data to assess respiratory function e.g. respiratory rate in breaths per minute, oxygen saturations in percentage, at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration, or equivalent in participating centers.
0-10 days from day of device application.
Standard-of-care temperature vital sign observation data
Time Frame: 0-10 days from day of device application.
Standard-of-care vital sign observation data to assess temperature e.g. in degrees centigrade or Fahrenheit, at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration or equivalent in participating centers.
0-10 days from day of device application.
Standard-of-care neurological observation data
Time Frame: 0-10 days from day of device application.
Standard-of-care vital sign observation data to assess neurological function e.g. Alert Verbal Pain Unresponsive (AVPU) at a frequency normally collected. These will be assessed as part of the National Early Warning Score 2 system (NEWS2) which a validated early warning score for detecting patient deterioration or equivalent in participating centres.
0-10 days from day of device application.
Incidence of clinical complications during the study period
Time Frame: 0-10 days from the day of device application and then 30 day follow up will be performed.
Incidence of clinical diagnosis data such as bleeding, major adverse cardiac event, sepsis will be derived from patient records and recorded and any uncertainty reviewed post hoc by an expert adjudication panel. Clinical complication data will also be gathered at 30 days.
0-10 days from the day of device application and then 30 day follow up will be performed.
Incidence of clinical investigations during the study period
Time Frame: 0-10 days from the day of device application.
The incidence of clinical investigations and descriptive details about the investigations will be derived from the patient records such as chest xray, CT abdomen, and wound swab.
0-10 days from the day of device application.
Incidence of clinical interventions during the study period
Time Frame: 0-10 days from the day of device application.
The incidence of clinical interventions performed and descriptive details, during the period of the device being worn will be recorded, e.g. commencement of antibiotics, unplanned admission to critical care, unplanned reoperation.
0-10 days from the day of device application.
Incidence and results of blood tests to assess patient physiological status during the study period
Time Frame: 0-10 days from the day of device application.
The incidence of blood tests will be recorded and the associated results from during the 10 day study period. Bloods tests recorded will include full blood count, urea and electrolytes, inflammatory markers, liver function tests and coagulation profile as well as blood gas results. They will be recorded using whichever the standard units are at participating centres.
0-10 days from the day of device application.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Edinburgh

Collaborators

Christian Medical College and Hospital, Ludhiana, India
University of Lagos, Nigeria
University of Birmingham
University of Rwanda
University for Development Studies, Tamale, Ghana
Hospital San Juan de Dios Guatemala
Hospital Español de Veracruz, Veracruz, Mexico
School of health sciences, University of Abomey Calavi, Benin

Investigators

  • Principal Investigator: Ewen Harrison, University of Edinburgh

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 28, 2024

Primary Completion (Estimated)

July 31, 2027

Study Completion (Estimated)

July 31, 2027

Study Registration Dates

First Submitted

July 15, 2024

First Submitted That Met QC Criteria

August 19, 2024

First Posted (Actual)

August 22, 2024

Study Record Updates

Last Update Posted (Actual)

February 10, 2026

Last Update Submitted That Met QC Criteria

February 6, 2026

Last Verified

February 1, 2026

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • EMUs
  • 13344828 (Other Grant/Funding Number: Wellcome Leap)

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

product manufactured in and exported from the U.S.

Yes

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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