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| Name | Class |
|---|---|
| Shanghai Shuli Intelligent Technology Co., Ltd | UNKNOWN |
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This study is a single-center, randomized controlled trial aiming to evaluate the analgesic mechanism of Transcutaneous Electrical Nerve Stimulation based on Wrist-Ankle Acupuncture (TENS-WAA) during unsedated colonoscopy using EEG-fNIRS technology to assess neural activity in brain regions associated with pain perception. Sixty patients aged 18-75 years, with stable cardiopulmonary function and a baseline visual analog scale (VAS) pain score <3, will be enrolled and randomly allocated into the intervention and control groups. The intervention group will receive TENS stimulation based on the Wrist-Ankle Acupuncture theory 10 minutes before the colonoscopy, with a frequency of 2 Hz and adjustable current intensity ranging from 1 to 9 mA. The control group will receive minimal-intensity sham stimulation under identical conditions. All participants will wear EEG-fNIRS devices to monitor neural activity in key pain-related brain areas, including the prefrontal cortex, anterior cingulate cortex, motor cortex, and parietal cortex. Primary outcomes include EEG-fNIRS data, while secondary outcomes are VAS scores at the four colonic bends, colonoscopy duration, and the correlation between EEG-fNIRS signals and pain perception. Statistical analyses will include multivariable linear regression, generalized estimating equations, and mixed-effects models to investigate the analgesic effects and neural mechanisms of TENS-WAA. This study seeks to provide innovative pain management strategies for patients undergoing unsedated colonoscopy and further explore the neuroregulatory potential of TENS-WAA technology.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Electrical stimulation group | Experimental | According to the WAA theory, the selected Lower Zone 1 (LZ1) and Lower Zone 2 (LZ2) are defined as follows: LZ1 is located between the medial Achilles tendon and the medial malleolus, while LZ2 is positioned at the central inner edge of the ankle joint, near the posterior border of the tibia. Two electrode pads will be placed on each LZ1 and LZ2 of both legs, totaling eight electrode pads. The TENS-WAA device will be set to a frequency of 2 Hz, a pulse width of 500 μs, and a continuous waveform. Participants in the stimulation group will receive electrical currents at their maximum tolerable intensity below the pain threshold. |
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| control group | Placebo Comparator | Participants in the control group will have the electrodes placed in the same positions as those in the stimulation group, with identical electrical stimulation frequency and pulse width settings. However, the current intensity will be set to the minimum level. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Using an electrical stimulation device to relieve pain during colonoscopy | Device | In the electrical stimulation group, the device's current intensity will be adjusted to the maximum tolerance below the participant's pain threshold, while in the control group, the current intensity will be set to the minimum. |
| Measure | Description | Time Frame |
|---|---|---|
| NeuroActivity Correlation Index | The NeuroActivity Correlation Index is a metric calculated using machine learning models to quantify the correlation between EEG and fNIRS data. Data preprocessing involves selecting appropriate frequency bands of EEG Power Spectral Density and corresponding brain regions' ΔHbO2 and ΔHb changes, with normalization of the data. Feature engineering involves extracting statistical and temporal window features, possibly using dimensionality reduction techniques such as Principal Component Analysis to enhance model efficiency. The model training phase utilizes regression models such as linear regression or support vector machine regression, or methods like Canonical Correlation Analysis to discover correlations between EEG and fNIRS data, optimizing model parameters through cross-validation. The correlation index is calculated based on model outcomes, typically expressed as a percentage, reflecting the statistical correlation strength between the datasets. | during procedure |
| Measure | Description | Time Frame |
|---|---|---|
| Pain VAS score | VAS is used to assess pain. It is widely used in clinical practice in China. The basic method is to use a 10-cm long floating ruler with 10 scale marks on one side, with 0 and 10 marks at the two ends. 0 means no pain, and 10 means the most severe pain that is unbearable. | during procedure (When the endoscope passes through the hepatic flexure, splenic area and rectosigmoid junction) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xiaonan Huang, master | Contact | 86+15700719913 | 1301090492@qq.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The First Affiliated Hospital of Naval Medical University | Recruiting | Shanghai | Shanghai Municipality | 200433 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41033775 | Derived | Wang H, Huang X, Xu L, Guo S, Gong C, Mengcheng C, Wang W, Wang H, Fang F. Analysis of the analgesic mechanism of TENS-WAA in colonoscopy using the EEG-fNIRS system: a study protocol for a randomised controlled trial. BMJ Open. 2025 Sep 30;15(9):e103681. doi: 10.1136/bmjopen-2025-103681. |
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De-identified individual participant data (IPD) that will be shared include:
Demographic information (age, sex, colonoscopy history)
Group allocation (TENS-WAA or sham stimulation)
Pain Visual Analogue Scale (VAS) scores at key time points
EEG and fNIRS raw and pre-processed data collected before, during, and after colonoscopy
Procedure duration and event timepoints (e.g., reaching hepatic flexure, splenic flexure, ileocecal valve)
Relevant clinical outcomes (e.g., adverse events, procedure completion status) The data will be available from the corresponding author upon reasonable request, following publication of the main results and with a signed data access agreement. No data that could directly identify individual participants will be shared.
The de-identified individual participant data (IPD) and supporting documents (such as data dictionaries and analysis code) will be available beginning 6 months after publication of the primary results article. Data will remain available for at least 5 years after publication, or longer if required by journal or institutional policy. Requests submitted after this period may be considered at the discretion of the corresponding author and study team.
Researchers from academic institutions, hospitals, or other recognized research organizations may access the de-identified individual participant data (IPD) and supporting documents (such as data dictionary and analysis code) for legitimate scientific research purposes by sending an email request to the corresponding author. The request should briefly describe the intended research use. All requests will be reviewed by the study team to ensure ethical compliance. Data sharing will require a signed data access agreement. Only de-identified data will be shared; no information that could directly identify participants will be provided.
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Before the trial begins, envelopes containing sequentially numbered cards from 1 to 60 will be prepared to determine participant allocation. The coordinator will open the envelopes in the order of participant enrollment. Throughout the trial, researchers are not allowed to alter the enrollment sequence. Participants will be informed in advance that they may experience electrical stimulation sensations, and communication between participants will be prohibited during the entire trial process. The statistician responsible for data analysis will remain blinded to the group allocation of participants.
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| Colonoscopy time | during procedure (The total time to reach the three bends and to the ileocecal valve and for the entire examination was recorded) |
| Correlation between EEG-fNIRS and pain VAS scores | The neurophysiological and hemodynamic indicators were correlated with pain scores using AI machine learning methods. | up to 24 weeks |
| ID | Term |
|---|---|
| D010146 | Pain |
| ID | Term |
|---|---|
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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