Horse Stress Analysis Using Biomechanical Modelling and Machine Learning Approach

被引:0
|
作者
AlZubi, Hamzah S. [1 ]
Al-Nuaimy, Waleed [1 ]
Young, Iain S. [2 ]
机构
[1] Univ Liverpool, Dept Elect Engn & Elect, Brownlow Hill, Liverpool L69 3GJ, Merseyside, England
[2] Univ Liverpool, Inst Integrat Biol, Crown St, Liverpool L69 7ZB, Merseyside, England
来源
2016 13TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD) | 2016年
关键词
Horse; Stress; Biomechanical model; Horse Transport; TRANSPORT;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Horse transport is a common practice in the equestrian industry, especially with the expansion of this industry around the world. Research has proved that horse transport by road is responsible for high stress levels, which sometimes exceed stress levels caused by exercising during professional horse races. Stress symptoms are reflected in the physiological functions of horses leading to horses suffering from horses fatigue or the injury. The horses stand still in a small box during transport to ensure safety and avoid falls or injuries. The weight is held by the four limbs while the vehicle is moving and vibration forces keep interrupting the balance. This requires the horse to counter these forces in order to keep its balance which demands high energy consumption even for short trips. The horse blood circulation system tries to support the muscles with enough oxygen forcing the heart to beat at high rates. This paper suggests an analytical biomechanical model for the vibration forces to understand how these forces move through horse limbs. This model is proposed to associate vibration forces with high stress levels during transport. Such a direct relationship between vehicle vibration forces and high stress levels will lead to a low cost non-invasive early stress detection system without the need to measure any direct physiological response of the horse. This relationship will also shed light on the importance of optimised vehicle design to reduce vibrations.
引用
收藏
页码:640 / 644
页数:5
相关论文
共 50 条
  • [21] Transcriptome signature for multiple biotic and abiotic stress in barley ( Hordeum vulgare L.) identifies using machine learning approach
    Panahi, Bahman
    CURRENT PLANT BIOLOGY, 2024, 40
  • [22] 3D Nanoscale Tracking Data Analysis for Intracellular Organelle Movement using Machine Learning Approach
    Lee, Seohyun
    Kim, Hyuno
    Ishikawa, Masatoshi
    Higuchi, Hideo
    2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (ICAIIC 2019), 2019, : 181 - 184
  • [23] Audio Signal Based Stress Recognition System using AI and Machine Learning
    Gupta, Megha
    Vaikole, Shubhangi
    JOURNAL OF ALGEBRAIC STATISTICS, 2022, 13 (02) : 1731 - 1740
  • [24] Development of a System to Detect Stress Using Electrocardiographic Signals and Machine Learning Models
    Vasquez-Ucho, Paola A.
    Valencia-Ramos, Rafael
    Villalba-Meneses, Fernando
    Tirado-Espin, Andres
    Salazar, Valeria Herrera
    Almeida-Galarraga, Diego
    2022 THIRD INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND SOFTWARE TECHNOLOGIES, ICI2ST, 2022, : 57 - 63
  • [25] Automatic Segmentation of Facial Regions of Interest and Stress Detection Using Machine Learning
    Jaramillo-Quintanar, Daniel
    Gomez-Reyes, Jean K.
    Morales-Hernandez, Luis A.
    Dominguez-Trejo, Benjamin
    Rodriguez-Medina, David A.
    Cruz-Albarran, Irving A.
    SENSORS, 2024, 24 (01)
  • [26] Physiological-Based Smart Stress Detector using Machine Learning Algorithms
    Rosales, Marife A.
    Bandala, Argel A.
    Vicerra, Ryan Rhay
    Dadios, Elmer P.
    2019 IEEE 11TH INTERNATIONAL CONFERENCE ON HUMANOID, NANOTECHNOLOGY, INFORMATION TECHNOLOGY, COMMUNICATION AND CONTROL, ENVIRONMENT, AND MANAGEMENT (HNICEM), 2019,
  • [27] A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques
    Gedam, Shruti
    Paul, Sanchita
    IEEE ACCESS, 2021, 9 : 84045 - 84066
  • [28] Machine Learning Based Stress Monitoring in Older Adults Using Wearable Sensors and Cortisol as Stress Biomarker
    Nath, Rajdeep Kumar
    Thapliyal, Himanshu
    Caban-Holt, Allison
    JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2022, 94 (06): : 513 - 525
  • [29] Machine Learning Based Stress Monitoring in Older Adults Using Wearable Sensors and Cortisol as Stress Biomarker
    Rajdeep Kumar Nath
    Himanshu Thapliyal
    Allison Caban-Holt
    Journal of Signal Processing Systems, 2022, 94 : 513 - 525
  • [30] An automated stress detection model based on dual approach of clinical psychologist prediction and machine learning
    Diptimoni Narzary
    Uzzal Sharma
    Ashish Khanna
    International Journal of Information Technology, 2025, 17 (2) : 755 - 765