Unveiling Physiological and Psychosocial Pain Components with an Artificial Intelligence Based Telemonitoring Tool (pAIn-sense)
Unveiling Physiological and Psychosocial Pain Components with an Artificial Intelligence Based Telemonitoring Tool (pAIn-sense)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Chronic pain has long been known as one of the major health concerns, impacting psychological health, functioning, and quality of life. However, its treatment is complex and is challenged by a complex interplay between biological, psychological, and social factors. Common pain treatments present significant medical and technological limitations, reflected in unspecific drug usage and an extremely high number of medical examinations that patients face regularly, with a huge cost burden on the healthcare system. Furthermore, the overall efficacy of pain management is often limited (73% dissatisfaction with treatment), leaving the patient in poor life conditions. Designing individualized targeted therapies requires understanding each subject's multidimensional pain experience, taking into consideration both the physical and emotional aspects involved. However, today, the golden standard measurement for pain is self-reports, which inherently suffer from subjective differences in perception and reporting. Healthcare systems advocate for the discovery of biomarkers and reliable clinical trial endpoints for pain to foster diagnosis, monitor pain progression, assess new treatments, and personalized therapeutic response. Nevertheless, most of the evidence today comes from inpatient settings or controlled laboratory environments. The pAIn-sense study aims at providing a radically novel approach in the monitoring and treatment of pain patients: a novel telemonitoring system allowing to understand the real nature of the pain (emotional vs physical), leveraging the use of advanced Artificial Intelligence techniques and wearable sensing technology collecting biometric data, therefore enabling efficient personalized treatments.
To achieve this goal, the investigators will combine real patient data both from a physical and emotional perspective, to characterize the pain nature of patients and provide a tailored continuum-of-care.
The system will include:
- Robotic wearable sensors (Hardware): wearable technology for physiological monitoring (e.g., skin conductance, blood volume pressure and heart rate, activity)
- Digital platform (Software): a customized application that collects psychological assessments, psychological status, medication, subjective pain level and sleep quality.
- AI-based engine: advanced AI models take all the previous physical and psychological information and model it to provide an outline of what is the nature of the pain level of the subject.
The system will be used to monitor the patient during normal activities (day and night) while collecting physiological, psychosocial, and pain information.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Andrea Cimolato, PhD
- Phone Number: +41 772466601
- Email: andrea.cimolato@gmail.com
Study Contact Backup
- Name: Noemi Gozzi
- Email: noemi.gozzi@gmail.com
Study Locations
-
-
Savona
-
Pietra Ligure, Savona, Italy, 17027
- Recruiting
- Unita Spinale ASL
-
Contact:
- Amy Bellito
- Phone Number: +393404273393
- Email: amybellito@gmail.com
-
-
-
-
-
Zurich, Switzerland, 8008
- Recruiting
- Balgrist University Hospital
-
Contact:
- Michele Hubli, PhD
-
-
Valais
-
Sion, Valais, Switzerland, 1950
- Recruiting
- CRR Suva (Clinique romande de réadaptation)
-
Contact:
- Bertrand Leger
- Phone Number: 0041 79 293 88 76
- Email: Bertrand.Leger@crr-suva.ch
-
-
Zurich
-
Zürich, Zurich, Switzerland, 8001
- Recruiting
- Neuroengineering Lab
-
Contact:
- Stanisa Raspopovic, PhD
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Ongoing nociceptive pain after an injury or Neuropathic pain (acute or chronic)
- Familiar with using electronic devices
Exclusion Criteria:
- Inability to follow the procedures of the study, e.g. due to language problems, psychological disorders, dementia, etc.
- Unable or not willing to give informed consent
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Control
Healthy controls
|
Observational study with no intervention - Monitoring
|
|
Pain
Patients suffering from acute/chronic nociceptive and neuropathic pain
|
Observational study with no intervention - Monitoring
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Pain level
Time Frame: Up to one month
|
Reported trough a digital health platform by the patients.
The level and its dynamic are monitored daily.
The pain level is recorded through a score from 1 to 10 that is reported trough a digital health platform by the patients.
|
Up to one month
|
|
Psychosocial components of pain experience through questionnaires
Time Frame: Up to one month
|
Monitored using the wearable technology and software digital platforms.
Questionnaires will be presented to the patients and will include anxiety, depression, fatigue, pain catastrophizing, sleep, awareness, pain efficacy, treatment expectation
|
Up to one month
|
|
Physiological components of pain and pain attacks in the physiological signals
Time Frame: Up to one month
|
Measured and extracted from wearable technology worn continuously.
Physiological biomarkers will include Skin Conductance (SC), blood volume pulse (BVP), Heart rate (HR), Brain signals (functional magnetic resonance imaging, electroencephalogram), movements (accelerometer, IMU), temperature.
|
Up to one month
|
|
Psychological and clinical factors affecting pain
Time Frame: Up to one month
|
Identified using questionnaires.
Scales are usually represented with values from 0 to 10 with 0 best outcome and 10 worst outcome.
|
Up to one month
|
|
Medication intake (rate and times per day)
Time Frame: Up to one month
|
As described in each patient's constant pain therapy or reported by the patient on request using the platform.
Medication will be measure in terms of rate of medications and changes during the protocols, times per day of intake, number of times a on-request medication is taken.
|
Up to one month
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Rehabilitation, physiotherapy and their effect
Time Frame: Up to one month
|
Correlation between rehabilitation or physiotherapy attendance and pain
|
Up to one month
|
|
Sleep, activity and other daily factors and their correlation with pain
Time Frame: Up to one month
|
Correlation between sleep, activity and other daily factors with pain (measured both from wearable technology and from patients report)
|
Up to one month
|
|
Predictors of chronification from acute phase
Time Frame: Up to one month
|
Identification and classification of physiological and psychosocial markers, that characterize transition between acute pain and chronic pain
|
Up to one month
|
|
Quality of Life and pain interference
Time Frame: Up to one month
|
QoL index done through questioners and how much pain interfere with the overall quality of life.
Scales from 0 to 10, with 10 better outcome and 0 worst outcome.
|
Up to one month
|
|
Responsiveness to medication
Time Frame: Up to one month
|
Changes in physiological biomarkers and pain perception following the intake of medication
|
Up to one month
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Stanisa Raspopovic, PhD, ETH Zurich
Publications and helpful links
General Publications
- Lotsch J, Ultsch A. Machine learning in pain research. Pain. 2018 Apr;159(4):623-630. doi: 10.1097/j.pain.0000000000001118. No abstract available.
- May M, Junghaenel DU, Ono M, Stone AA, Schneider S. Ecological Momentary Assessment Methodology in Chronic Pain Research: A Systematic Review. J Pain. 2018 Jul;19(7):699-716. doi: 10.1016/j.jpain.2018.01.006. Epub 2018 Jan 31.
- Cohen SP, Vase L, Hooten WM. Chronic pain: an update on burden, best practices, and new advances. Lancet. 2021 May 29;397(10289):2082-2097. doi: 10.1016/S0140-6736(21)00393-7.
- Tracey I, Woolf CJ, Andrews NA. Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment. Neuron. 2019 Mar 6;101(5):783-800. doi: 10.1016/j.neuron.2019.02.019.
- Davis KD, Aghaeepour N, Ahn AH, Angst MS, Borsook D, Brenton A, Burczynski ME, Crean C, Edwards R, Gaudilliere B, Hergenroeder GW, Iadarola MJ, Iyengar S, Jiang Y, Kong JT, Mackey S, Saab CY, Sang CN, Scholz J, Segerdahl M, Tracey I, Veasley C, Wang J, Wager TD, Wasan AD, Pelleymounter MA. Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities. Nat Rev Neurol. 2020 Jul;16(7):381-400. doi: 10.1038/s41582-020-0362-2. Epub 2020 Jun 15.
- Kratz AL, Ehde DM, Bombardier CH, Kalpakjian CZ, Hanks RA. Pain Acceptance Decouples the Momentary Associations Between Pain, Pain Interference, and Physical Activity in the Daily Lives of People With Chronic Pain and Spinal Cord Injury. J Pain. 2017 Mar;18(3):319-331. doi: 10.1016/j.jpain.2016.11.006. Epub 2016 Dec 2.
- Volkow ND, McLellan AT. Opioid Abuse in Chronic Pain--Misconceptions and Mitigation Strategies. N Engl J Med. 2016 Mar 31;374(13):1253-63. doi: 10.1056/NEJMra1507771. No abstract available.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 2021-01814
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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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