SPA: Smart Pain Assesment Tool Based on Internet of Things
Study Details
Study Description
Brief Summary
This study is the second phase of a research project called "Smart Pain Assessment Tool based on Internet-of-Things". During the course of this project, a smart pain assessment tool (SPA) to detect and assess pain employing behavioural and physiologic indicators will be developed. We aim to assess pain based on changes in electromyographic (EMG) activity in facial muscles, i.e. changes in facial expressions and simultaneously use physiologic signs such as heart rate, respiratory rate and galvanic skin response as adjuvant measures to develop an algorithm for pain assessment in critically ill patients.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
The aim of this "smart pain assessment tool based on internet of things" SPA-research project is to develop an automatic and versatile pain assessment tool algorithm for detection and assessment of pain in a reliable and objective way in non-communicative patients. The final objective of the research project is to develop a smart pain assessment tool to detect and assess pain employing behavioural and physiologic indicators for a wide range of users/patients from infants to elderly people who are unable to communicate normally. The research project consists of three clinical phases (European Commision. Meddev 2.7/4/2010). The clinical phase I of the research project focused on developing pain assessment techniques involuntary working-age healthy study subjects. This current Clinical phase II includes the further development and research of the smart pain assessment tool in elective (non emergency) postoperative surgical patients during their stay after surgery in a recovery room.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Postoperative patients We recruit postoperative patients who undergo open surgery and are not receiving local anesthesia. We install a smart pain assessment tool on patient's skin to capture different type of data. |
Device: Smart pain assessment tool
We record and analyze multiple bio-signals from post-operative patients in the attempt to evaluate their experienced pain.
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Outcome Measures
Primary Outcome Measures
- Facial muscle activity [2 hours after surgery when the subject has woken up]
The device is designed for multi-channel EMG acquisition from facial skin. Measuring a combination of EMG signals and their energy level (amplitude).
Secondary Outcome Measures
- Skin conductance [2 hours after surgery when the subject has woken up]
Galvanic skin response (GSR), also known as electrodermal activity (EDA) or skin conductance (SC).
- Pain assesment by VAS [2 hours after surgery when the subject has woken up]
Subjective feeling of pain is asked every 10 minutes by using numeric visual analog scale (VAS), values are given from 0-10.
- Heart rate [2 hours after surgery when the subject has woken up]
Heart rate is monitored and recorded.
- Respiratory rate [2 hours after surgery when the subject has woken up]
Respiratory rate is monitored and recorded.
- Oxygen saturation [2 hours after surgery when the subject has woken up]
Oxygen saturation is monitored and recorded.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Subject is scheduled for major surgery that requires general anesthesia and is likely to cause moderate to severe pain postoperatively which needs to be treated with systemic analgesics
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Ability to communicate
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Written informed consent
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Healthy facial skin
Exclusion Criteria:
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Subject treated with local anesthesia during surgery
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Any diagnosed condition affecting cognitive functions
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Surgery affecting hands where pulse oximetry and galvanic skin reaction are recorded or areas where facial muscle activity is measured
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Any diagnosed condition affecting central nervous system, facial nerves or muscles.
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Significant facial hair growth in the area where the sensors will be attached
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Tattoos in the area where the sensors will be attached
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | University of Turku | Turku | Finland | 20140 |
Sponsors and Collaborators
- University of Turku
- Academy of Finland
- Turku University Hospital
Investigators
- Principal Investigator: Sanna Salanterä, Prof, University of Turku
Study Documents (Full-Text)
None provided.More Information
Publications
- EPoSS. 2008. Internet of Things in 2020: a Roadmap for the Future. European Technology Platform on Smart Systems Integration. European Commission Information Society.
- Jeitziner MM, Schwendimann R, Hamers JP, Rohrer O, Hantikainen V, Jakob SM. Assessment of pain in sedated and mechanically ventilated patients: an observational study. Acta Anaesthesiol Scand. 2012 May;56(5):645-54. doi: 10.1111/j.1399-6576.2012.02660.x. Epub 2012 Mar 7.
- Ledowski T, Ang B, Schmarbeck T, Rhodes J. Monitoring of sympathetic tone to assess postoperative pain: skin conductance vs surgical stress index. Anaesthesia. 2009 Jul;64(7):727-31. doi: 10.1111/j.1365-2044.2008.05834.x. Epub 2009 Jan 28.
- Prkachin KM. Assessing pain by facial expression: facial expression as nexus. Pain Res Manag. 2009 Jan-Feb;14(1):53-8. Review.
- Viertiö-Oja H, Maja V, Särkelä M, Talja P, Tenkanen N, Tolvanen-Laakso H, Paloheimo M, Vakkuri A, Yli-Hankala A, Meriläinen P. Description of the Entropy algorithm as applied in the Datex-Ohmeda S/5 Entropy Module. Acta Anaesthesiol Scand. 2004 Feb;48(2):154-61.
- 29092016