Abstract Every year, many people lose their lives because of road accidents. It is evident from statistics that drowsiness is one of the main causes of a large number of car accidents. In our research, we wish to solve this major problem by measuring the drowsiness level of the human brain while driving. The study aims to develop a novel technique to detect different alertness levels (i.e., awake, moderately drowsy, and maximally drowsy) of a person while driving. A hybrid model using a stacked autoencoder and hyperbolic tangent Long Short‐Term Memory (TLSTM) network with attention mechanism is designed for this purpose. The designed model uses different biopotential signals, such as electroencephalography (EEG), facial electromyography (EMG), and different biomarkers, such as pulse rate, respiration rate galvanic skin response, and head movement to detect a person's alertness level. Here, the stacked autoencoder model is used for automated feature extraction. TLSTM is used to predict a person's alertness level using stacked autoencoder network‐extracted features. The proposed model can classify awake, moderately drowsy, and maximally drowsy states of a person with accuracies of 99%, 98.3%, and 98.6%, respectively. The novel contributions of the paper includes (i) incorporation of an attention mechanism into the TLSTM network of the proposed hybrid model to focus on the emphatic states to enhance classification accuracy, and (ii) utilization of EEG, facial EMG, pulse rate, respiration rate, galvanic skin reaction, and head movement pattern to assess a person's alertness level.

Prithwijit Mukherjee

Anisha Halder Roy

Human Factors and Ergonomics in Manufacturing & Service Industries

制造和服务行业中的人为因素和人体工程学的目的是促进有关制造中人的方面的科学知识的发现、整合和应用，并为全球传播此类知识以使其应用和造福于制造业提供一个论坛。该杂志涵盖了广泛的人体工程学和人为因素问题，重点关注车间和办公环境中当代制造系统的设计、运营和管理，以寻求制造敏捷性，即增强和整合人类技能具有提高市场竞争力的硬件性能、变更管理、产品和过程质量以及人类系统的可靠性。该期刊的跨学科性质允许与制造系统设计和工程、人力资源管理、社会、组织、安全和健康问题相关的广泛问题。感兴趣的具体学科领域的例子包括：先进制造技术的实施、计算机辅助设计和工程的人的方面、工作设计、薪酬和评估、选拔培训和教育、劳资关系、敏捷制造和虚拟公司、人为因素在全面质量管理、预防与工作相关的肌肉骨骼疾病、工作场所的人体工程学、设备和工具设计、人体工程学计划、工业指南和标准、自动化安全和机器人系统、人类技能发展和知识增强技术、可靠性和安全性和工人健康问题。

The journal "Human Factors and Ergonomics in Manufacturing and Service Industries" aims to promote the discovery, integration, and application of scientific knowledge regarding the human aspects of manufacturing and service industries, providing a forum for the global dissemination of such knowledge to enhance its application and benefits in the manufacturing sector. This journal covers a wide range of issues related to ergonomics and human factors, focusing on the design, operation, and management of contemporary manufacturing systems in workshop and office environments, seeking to enhance manufacturing agility by integrating and augmenting human skills to improve market competitiveness, hardware performance, change management, product and process quality, and the reliability of human systems. The interdisciplinary nature of the journal allows for the exploration of a broad spectrum of issues related to the design and engineering of manufacturing systems, human resource management, social, organizational, safety, and health concerns. Specific areas of interest include the implementation of advanced manufacturing technologies, the human aspects of computer-aided design and engineering, work design, compensation and evaluation, selection training and education, labor relations, agile manufacturing and virtual companies, human factors in total quality management, prevention of work-related musculoskeletal disorders, workplace ergonomics, equipment and tool design, ergonomics programs, industrial guidelines and standards, automation safety and robotic systems, human skill development and knowledge enhancement technologies, reliability and safety, and worker health issues.

《Human Factors and Ergonomics in Manufacturing and Service Industries》期刊旨在促进制造和服务行业中人与系统之间的科学知识的发现、整合和应用，并为全球传播此类知识提供一个论坛，以便更好地应用于制造业。该杂志涵盖广泛的人体工程学和人为因素问题，重点关注现代制造系统在车间和办公环境中的设计、运营和管理，旨在提升制造的灵活性，即通过增强和整合人类技能来提高市场竞争力、硬件性能、变更管理、产品和过程质量以及人类系统的可靠性。期刊的跨学科性质使其能够探讨与制造系统设计和工程、人力资源管理、社会、组织、安全和健康等相关的广泛问题。具体感兴趣的学科领域包括：先进制造技术的实施、计算机辅助设计和工程中的人为因素、工作设计、薪酬与评估、选拔培训与教育、劳资关系、敏捷制造与虚拟公司、全面质量管理中的人为因素、预防与工作相关的肌肉骨骼疾病、工作场所的人体工程学、设备与工具设计、人体工程学计划、工业指南与标准、自动化安全与机器人系统、人类技能发展与知识增强技术、可靠性与安全性以及工人健康问题。

Category	Quartile
工程技术	3
工程技术, 工程制造	4
工程技术, 人体工程学	4

A novel deep learning‐based technique for driver drowsiness detection

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