Operative video has great potential to enable instant replays of critical surgical decisions for training and quality review. Recently, artificial intelligence (AI) has shown early promise as a method of enabling efficient video review, analysis, and segmentation. Despite the progress with AI analysis of surgical videos, more work needs to be done to improve the accuracy and efficiency of AI-driven video analysis. At a recent consensus conference held on July 10-11, 2020, 8 research teams shared their work using AI for surgical video analysis. Four of the teams showcased the utility of wearable technology in providing objective surgical metrics. Data from these technologies were shown to pinpoint important cognitive and motor actions during operative tasks and procedures. The results support the utility of wearable technology to facilitate efficient and accurate video analysis and segmentation.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455149PMC
http://dx.doi.org/10.1097/AS9.0000000000000011DOI Listing

Publication Analysis

Top Keywords

wearable technology
12
video analysis
12
technology facilitate
8
analysis surgical
8
surgical videos
8
analysis segmentation
8
utility wearable
8
analysis
6
surgical
5
video
5

Similar Publications

Smart textiles provide a significant technological advancement, but their development must balance traditional textile properties with electronic features. To address this challenge, this study introduces a flexible, electrically conductive composite material that can be fabricated using a continuous bi-component extrusion process, making it ideal for sensor electrodes. The primary aim was to create a composite for the filament's core, combining multi-walled carbon nanotubes (MWCNTs), polypropylene (PP), and thermoplastic elastomer (TPE), optimised for conductivity and flexibility.

View Article and Find Full Text PDF

Time-Series Image-Based Automated Monitoring Framework for Visible Facilities: Focusing on Installation and Retention Period.

Sensors (Basel)

January 2025

Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Yongin-si 16890, Republic of Korea.

In the construction industry, ensuring the proper installation, retention, and dismantling of temporary structures, such as jack supports, is critical to maintaining safety and project timelines. However, inconsistencies between on-site data and construction documentation remain a significant challenge. To address this, this study proposes an integrated monitoring framework that combines computer vision-based object detection and document recognition techniques.

View Article and Find Full Text PDF

Depression Recognition Using Daily Wearable-Derived Physiological Data.

Sensors (Basel)

January 2025

Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing 100084, China.

The objective identification of depression using physiological data has emerged as a significant research focus within the field of psychiatry. The advancement of wearable physiological measurement devices has opened new avenues for the identification of individuals with depression in everyday-life contexts. Compared to other objective measurement methods, wearables offer the potential for continuous, unobtrusive monitoring, which can capture subtle physiological changes indicative of depressive states.

View Article and Find Full Text PDF

Action Recognition in Basketball with Inertial Measurement Unit-Supported Vest.

Sensors (Basel)

January 2025

Computer Engineering Department, Engineering Faculty, Aydın Adnan Menderes University, Aydın 09100, Türkiye.

In this study, an action recognition system was developed to identify fundamental basketball movements using a single Inertial Measurement Unit (IMU) sensor embedded in a wearable vest. This study aims to enhance basketball training by providing a high-performance, low-cost solution that minimizes discomfort for athletes. Data were collected from 21 collegiate basketball players, and movements such as dribbling, passing, shooting, layup, and standing still were recorded.

View Article and Find Full Text PDF

Over the past ten years, there has been an increasing demand for reliable consumer wearables as users are inclined to monitor their health and fitness metrics in real-time, especially since the COVID-19 pandemic. Reflectance pulse oximeters in fitness trackers and smartwatches provide convenient, non-invasive SpO measurements but face challenges in achieving medical-grade accuracy, particularly due to difficulties in capturing physiological signals, which may be affected by skin pigmentation. Hence, this study sets out to investigate the influence of skin pigmentation, particularly in individuals with darker skin, on the accuracy and reliability of SpO measurement in consumer wearables that utilise reflectance pulse oximeters.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!