Irregular surface temperature monitoring in liver procurement via time-vertex signal processing DOI
Sahand Hajifar, Hongyue Sun

IISE Transactions on Healthcare Systems Engineering, Год журнала: 2024, Номер 14(4), С. 346 - 361

Опубликована: Авг. 17, 2024

The liver viability monitoring during its procurement is critical to guarantee the safe transportation. Traditionally, assessed by taking invasive biopsy on surface. Recently, noninvasive thermal images of surface have been used as an alternative assessment way. Researchers proposed and classification approaches based images. Existing works demonstrated importance temporal variation or spatial monitoring. However, there no prior work leverage graph structure spatio-temporal processes for In this paper, we propose a time-vertex signal processing framework irregular data pure region particular, extract features joint Fourier transform (JFT), which integration (GFT) discrete (DFT). extracted JFT can accurately reconstruct with limited number features. Then, use non-parametric online change-point estimation method, scan B statistics, monitor without parametric distribution. Our applied both simulation data, achieves good performance.

Язык: Английский

Machine learning assisted human fatigue detection, monitoring, and recovery: A Review DOI Creative Commons

Arsalan Lambay,

Ying Liu, Phillip L. Morgan

и другие.

Digital engineering., Год журнала: 2024, Номер 1, С. 100004 - 100004

Опубликована: Май 23, 2024

The use of knowledge-based information systems to improve human performance has been limited by a lack comprehension how an individual's diminishes when fatigue accumulates, which might vary between individuals depending on their working environment. Although the rise in automation witnessed, there are still some physically demanding and exhausting jobs manufacturing environment that, if not appropriately managed, can result long-term issues including musculoskeletal disorders impairments psychological well-being. To detect, comprehend manage development solutions for detection, Machine Learning (ML) useful tool. This paper presents review ML techniques detection monitoring operator's work-related physical repetitive work Human-Robot Collaboration (HRC) settings. novel offers overview complexity manufacturing-related contexts. three major components: First, level with help ML, only specific influencing factors terms features selected that concerning tasks context fatigue. Second, generated relation while operating under conditions included - worker detecting technology. Finally, challenges limitations holistic approaches monitoring/recovery essence exertion individual critically discussed.

Язык: Английский

Процитировано

6
Irregular surface temperature monitoring in liver procurement via time-vertex signal processing DOI
Sahand Hajifar, Hongyue Sun

IISE Transactions on Healthcare Systems Engineering, Год журнала: 2024, Номер 14(4), С. 346 - 361

Опубликована: Авг. 17, 2024

The liver viability monitoring during its procurement is critical to guarantee the safe transportation. Traditionally, assessed by taking invasive biopsy on surface. Recently, noninvasive thermal images of surface have been used as an alternative assessment way. Researchers proposed and classification approaches based images. Existing works demonstrated importance temporal variation or spatial monitoring. However, there no prior work leverage graph structure spatio-temporal processes for In this paper, we propose a time-vertex signal processing framework irregular data pure region particular, extract features joint Fourier transform (JFT), which integration (GFT) discrete (DFT). extracted JFT can accurately reconstruct with limited number features. Then, use non-parametric online change-point estimation method, scan B statistics, monitor without parametric distribution. Our applied both simulation data, achieves good performance.

Язык: Английский

Процитировано

0