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「危険作業現場を変えるデジタル技術、48研究から見えた可能性と課題」の検索結果

87 件中 10 件を表示 (4143 ms) · ⭐ 保存した論文

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("occupational safety"[MeSH] OR "workplace safety" OR "hazardous work" OR "dangerous work") AND ("digital technology" OR "digitalization" OR IoT OR "artificial intelligence" OR sensors OR wearables OR "augmented reality" OR VR)

💡 危険作業現場の安全とデジタル技術の組み合わせで検索。IoT、AI、センサー、AR/VR等の具体的技術も含めて網羅性を確保

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🔍 PubMed の検索結果

  • Personalized Activity Recognition with Deep Triplet Embeddings.

    David Burns, Philip Boyer, Colin Arrowsmith 他 · Sensors (Basel, Switzerland) · 2022

    A significant challenge for a supervised learning approach to inertial human activity recognition is the heterogeneity of data generated by individual users, resulting in very poor performance for some subjects. We present an approach to personalized activity recognition based on deep feature representation derived from a convolutional neural network (CNN). We experiment with both categorical cros…

    📄 PubMed で読む (PMID: 35890902)
  • ADA-SR: Activity detection and analysis using security robots for reliable workplace safety.

    Guangnan Zhang, Wang Jing, Hai Tao 他 · Work (Reading, Mass.) · 2021

    Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease. This paper discusses activity detection and analysis (ADA) using security r…

    📄 PubMed で読む (PMID: 33612535)
  • Out-of-Distribution Detection of Human Activity Recognition with Smartwatch Inertial Sensors.

    Philip Boyer, David Burns, Cari Whyne 他 · Sensors (Basel, Switzerland) · 2021

    Out-of-distribution (OOD) in the context of Human Activity Recognition (HAR) refers to data from activity classes that are not represented in the training data of a Machine Learning (ML) algorithm. OOD data are a challenge to classify accurately for most ML algorithms, especially deep learning models that are prone to overconfident predictions based on in-distribution (IIN) classes. To simulate th…

    📄 PubMed で読む (PMID: 33804317)
  • Integrating Information Technologies Safety Into Occupational and Environmental Safety Management Systems.

    Martín-José Sepúlveda · Journal of occupational and environmental medicine · 2019

    To discuss the need for the inclusion of decision-support software safety in workplace safety management systems. Review of software safety systems, the socio-technical model of Information Technologies safety and sources of decision-support software safety risk. Not applicable to a commentary viewpoint article. There are no regulatory safety standards for decision-support software as there are fo…

    📄 PubMed で読む (PMID: 31166283)
  • How Effective Are Forecasting Models in Predicting Effects of Exoskeletons on Fatigue Progression?

    Pranav Madhav Kuber, Abhineet Rajendra Kulkarni, Ehsan Rashedi 他 · Sensors (Basel, Switzerland) · 2024

    Forecasting can be utilized to predict future trends in physiological demands, which can be beneficial for developing effective interventions. This study implemented forecasting models to predict fatigue level progression when performing exoskeleton (EXO)-assisted tasks. Specifically, perceived and muscle activity data were utilized from nine recruited participants who performed 45° trunk flexion …

    📄 PubMed で読む (PMID: 39338720)
  • Quantifying the Relationship Between At-Home Shoulder Physiotherapy Participation and Outcome: What can a Watch Tell Us?

    Philip Boyer, David Burns, Helen Razmjou 他 · The Journal of the American Academy of Orthopaedic Surgeons · 2025

    Exercise-based physiotherapy is an established treatment of rotator cuff injury. Objective assessment of at-home exercise is critical to understand its relationship with clinical outcomes. This study uses the Smart Physiotherapy Activity Recognition System to measure at-home physiotherapy participation in patients with rotator cuff injury based on inertial sensor data captured from smart watches. …

    📄 PubMed で読む (PMID: 39888607)
  • Heterojunctions of rGO/Metal Oxide Nanocomposites as Promising Gas-Sensing Materials-A Review.

    Mohd Nurazzi Norizan, Norli Abdullah, Norhana Abdul Halim 他 · Nanomaterials (Basel, Switzerland) · 2022

    Monitoring environmental hazards and pollution control is vital for the detection of harmful toxic gases from industrial activities and natural processes in the environment, such as nitrogen dioxide (NO2), ammonia (NH3), hydrogen (H2), hydrogen sulfide (H2S), carbon dioxide (CO2), and sulfur dioxide (SO2). This is to ensure the preservation of public health and promote workplace safety. Graphene a…

    📄 PubMed で読む (PMID: 35808113)
  • Employee acceptance of wearable technology in the workplace.

    Jesse V Jacobs, Lawrence J Hettinger, Yueng-Hsiang Huang 他 · Applied ergonomics · 2019

    Wearable technology has many industrial applications. Optimal use adherence and outcomes largely depend on employee acceptance of the technology. This study determined factors that predict employee acceptance of wearables. An online survey of 1273 employed adults asked about demographics, job and organizational characteristics, experience with and beliefs about wearables, and willingness to use we…

    📄 PubMed で読む (PMID: 31046946)
  • Current State of Laboratory Automation in Clinical Microbiology Laboratory.

    Kritikos Antonios, Antony Croxatto, Karissa Culbreath 他 · Clinical chemistry · 2021

    Although it has been 30 years since the first automation systems were introduced in the microbiology laboratory, total laboratory automation (TLA) has only recently been recognized as a valuable component of the laboratory. A growing number of publications illustrate the potential impact of automation. TLA can improve standardization, increase laboratory efficiency, increase workplace safety, and …

    📄 PubMed で読む (PMID: 34969105)
  • Heterogeneous Autonomous Robotic System in Viticulture and Mariculture: Vehicles Development and Systems Integration.

    Nadir Kapetanović, Jurica Goričanec, Ivo Vatavuk 他 · Sensors (Basel, Switzerland) · 2022

    There are activities in viticulture and mariculture that require extreme physical endurance from human workers, making them prime candidates for automation and robotization. This paper presents a novel, practical, heterogeneous, autonomous robotic system divided into two main parts, each dealing with respective scenarios in viticulture and mariculture. The robotic components and the subsystems tha…

    📄 PubMed で読む (PMID: 35458946)