Screening of OSA in Hospitalized Stroke Patients Using BSP

NCT ID: NCT05466864

Last Updated: 2022-07-20

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: NA
• Total Enrollment: 120 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-05-04
• Study Completion Date: 2024-05-03

Brief Summary

Obstructive sleep apnea (OSA) is prevalent in patients with stroke and has a negative effect on outcomes by predisposing them to recurrent stroke, increasing mortality, and so forth. Therefore, it is extremely important to identify OSA in patients with stroke.

Wearable devices can greatly reduce the manpower and material requirements of traditional laboratory-based polysomnography (PSG). With Photoplethysmography (PPG) technology and neural network algorithms, the Belun ring and the sleeping platform not only can detect blood oxygen, and heart rate but also can identify sleep stage and estimate the severity of sleep apnea.

In this study, inpatients with acute ischemic stroke in the hospital will proceed with three nights test for recording the parameters of the autonomic nervous system in the acute phase, evaluate whether sleep apnea and the feasibility of the Belun sleep platform.

It is important that early recognition of OSA and prompt treatment, which can potentially improve OSA-associated adverse outcomes, as well as understanding the degree of autonomic nervous function impairment for patients with acute ischemic stroke. After smoothing this process, it can help clinicians more accurately comprehend the condition, timing of admission, and discharge.

Conditions

Sleep-Disordered Breathing; Sleep Architecture; Stroke, Acute

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

TMU Hospital

Potential participants with suspected OSA will be identified from the schedule of the TMU sleep labs. Those subjects who satisfy the study conclusion and exclusion criteria will be approached and invited to participate in the study.

Group Type: EXPERIMENTAL

Belun Sleep platform

Intervention Type: DEVICE

BSP(Belun Technology Company Limited) is a novel wearable system using a neural network algorithm that consists of a patented wearable device (Belun Ring), a charging cradle, and cloud-based software. The Belun Ring, an FDA-cleared pulse oximeter, acquires signals from the radialis indicis artery of the proximal index finger. The Belun Ring total sleep time can be derived from features extracted from accelerometer, SpO2, and PPG signals, whereas Belun Ring AHI can be derived from Ring-TST and features extracted from HRV and SpO2 changes. The BSP proprietary OSA detection algorithm was using neural network. BSP performance can be improved by training the algorithm through continual data collection. To our knowledge, BSP is the only validated sleep platform using a medical-grade wearable pulse oximeter, actigraphy, and artificial intelligence algorithm that has the capability to identify sleep stages, detect OSA events, and monitor autonomic nervous system activity changes during sleep.

Interventions

Belun Sleep platform

BSP(Belun Technology Company Limited) is a novel wearable system using a neural network algorithm that consists of a patented wearable device (Belun Ring), a charging cradle, and cloud-based software. The Belun Ring, an FDA-cleared pulse oximeter, acquires signals from the radialis indicis artery of the proximal index finger. The Belun Ring total sleep time can be derived from features extracted from accelerometer, SpO2, and PPG signals, whereas Belun Ring AHI can be derived from Ring-TST and features extracted from HRV and SpO2 changes. The BSP proprietary OSA detection algorithm was using neural network. BSP performance can be improved by training the algorithm through continual data collection. To our knowledge, BSP is the only validated sleep platform using a medical-grade wearable pulse oximeter, actigraphy, and artificial intelligence algorithm that has the capability to identify sleep stages, detect OSA events, and monitor autonomic nervous system activity changes during sleep.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Hospitalized patients with confirmed acute ischemic stroke
• Age 18-80
• Able to consent

Exclusion Criteria

• History of atrial fibrillation, LVEF < 45%, pacemaker/defibrillator, left ventricular assist device (LVAD), or status post-cardiac transplantation, devastating strokes ( mRS >= 4).
• Aphasia, severe bulbar palsy, unable to comprehend, consent, or answer questionnaires.
• Unstable cardiopulmonary status.
• Recent surgery including tracheotomy in 30 days.
• On narcotics.
• On O2, PAP device, ventilator, diaphragmatic pacing, or any form of nerve stimulator
• unable to understand instructions or to accurately use BRP during the instruction session.
• Patients with technically valid recording time under 4 hours will be excluded.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Case Western Reserve University

OTHER

Sponsor Role: collaborator

Taipei Medical University Shuang Ho Hospital

OTHER

Sponsor Role: lead

Responsible Party

Wen-De Liu

Director of Sleep Center

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Wen-Te Liu, MD. PhD

Role: STUDY_DIRECTOR

Taipei Medical University Shuang Ho Hospital

Locations

Taipei Medical University Shuang Ho Hospital

New Taipei City, , Taiwan

Site Status: RECRUITING

Countries

Taiwan

Central Contacts

Wen-Te Liu, MD. PhD

Role: CONTACT

b7801077@tmu.edu.tw

+886-222490088 ext. 72431

Facility Contacts

Wen-Te Liu, MD. PhD

Role: primary

b7801077@tmu.edu.tw

+886-222490088 ext. 72431

Other Identifiers

N202203152

Identifier Type: -

Identifier Source: org_study_id