These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

186 related articles for article (PubMed ID: 33917206)

  • 1. Work-Related Risk Assessment According to the Revised NIOSH Lifting Equation: A Preliminary Study Using a Wearable Inertial Sensor and Machine Learning.
    Donisi L; Cesarelli G; Coccia A; Panigazzi M; Capodaglio EM; D'Addio G
    Sensors (Basel); 2021 Apr; 21(8):. PubMed ID: 33917206
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Logistic Regression Model for Biomechanical Risk Classification in Lifting Tasks.
    Donisi L; Cesarelli G; Capodaglio E; Panigazzi M; D'Addio G; Cesarelli M; Amato F
    Diagnostics (Basel); 2022 Oct; 12(11):. PubMed ID: 36359468
    [TBL] [Abstract][Full Text] [Related]  

  • 3. sEMG Spectral Analysis and Machine Learning Algorithms Are Able to Discriminate Biomechanical Risk Classes Associated with Manual Material Liftings.
    Donisi L; Jacob D; Guerrini L; Prisco G; Esposito F; Cesarelli M; Amato F; Gargiulo P
    Bioengineering (Basel); 2023 Sep; 10(9):. PubMed ID: 37760205
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Capability of Machine Learning Algorithms to Classify Safe and Unsafe Postures during Weight Lifting Tasks Using Inertial Sensors.
    Prisco G; Romano M; Esposito F; Cesarelli M; Santone A; Donisi L; Amato F
    Diagnostics (Basel); 2024 Mar; 14(6):. PubMed ID: 38535000
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach.
    Conforti I; Mileti I; Del Prete Z; Palermo E
    Sensors (Basel); 2020 Mar; 20(6):. PubMed ID: 32168844
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A multiple linear regression approach to extimate lifted load from features extracted from inertial data.
    Donisi L; Capodaglio EM; Amitrano F; Cesarelli G; Pagano G; D'Addio G
    G Ital Med Lav Ergon; 2021 Dec; 43(4):373-378. PubMed ID: 35049162
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The accuracy of a 2D video-based lifting monitor.
    Wang X; Hu YH; Lu ML; Radwin RG
    Ergonomics; 2019 Aug; 62(8):1043-1054. PubMed ID: 31092146
    [TBL] [Abstract][Full Text] [Related]  

  • 8. The National Institute for Occupational Safety and Health (NIOSH) Recommended Weight Generates Different Spine Loads in Load-Handling Activity Performed Using Stoop, Semi-squat and Full-Squat Techniques; a Full-Body Musculoskeletal Model Study.
    Dehghan P; Arjmand N
    Hum Factors; 2024 May; 66(5):1387-1398. PubMed ID: 36433743
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Biomechanical Assessment of the NIOSH Lifting Equation in Asymmetric Load-Handling Activities Using a Detailed Musculoskeletal Model.
    Behjati M; Arjmand N
    Hum Factors; 2019 Mar; 61(2):191-202. PubMed ID: 30222936
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison of different lifting analysis tools in estimating lower spinal loads - Evaluation of NIOSH criterion.
    Ghezelbash F; Shirazi-Adl A; Plamondon A; Arjmand N
    J Biomech; 2020 Nov; 112():110024. PubMed ID: 32961423
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Mechanical lifting energy consumption in work activities designed by means of the "revised NIOSH lifting equation".
    Ranavolo A; Varrecchia T; Rinaldi M; Silvetti A; Serrao M; Conforto S; Draicchio F
    Ind Health; 2017 Oct; 55(5):444-454. PubMed ID: 28781290
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Understanding outcome metrics of the revised NIOSH lifting equation.
    Fox RR; Lu ML; Occhipinti E; Jaeger M
    Appl Ergon; 2019 Nov; 81():102897. PubMed ID: 31422239
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Analysis of manual lifting tasks: a qualitative alternative to the NIOSH work practices guide.
    Keyserling WM
    Am Ind Hyg Assoc J; 1989 Mar; 50(3):165-73. PubMed ID: 2718910
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting the load constant of the revised NIOSH lifting equation based on demographics.
    Ahmad S; Muzammil M
    Int J Occup Saf Ergon; 2023 Sep; 29(3):1016-1024. PubMed ID: 35758150
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Use of a wearable electromyography armband to detect lift-lower tasks and classify hand loads.
    Taori S; Lim S
    Appl Ergon; 2024 Sep; 119():104285. PubMed ID: 38797013
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automation of workplace lifting hazard assessment for musculoskeletal injury prevention.
    Spector JT; Lieblich M; Bao S; McQuade K; Hughes M
    Ann Occup Environ Med; 2014; 26():15. PubMed ID: 24987523
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Improving the risk assessment capability of the revised NIOSH lifting equation by incorporating personal characteristics.
    Barim MS; Sesek RF; Capanoglu MF; Drinkaus P; Schall MC; Gallagher S; Davis GA
    Appl Ergon; 2019 Jan; 74():67-73. PubMed ID: 30487111
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Efficacy of the revised NIOSH lifting equation to predict risk of low-back pain associated with manual lifting: a one-year prospective study.
    Lu ML; Waters TR; Krieg E; Werren D
    Hum Factors; 2014 Feb; 56(1):73-85. PubMed ID: 24669544
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Wearable Monitoring Devices for Biomechanical Risk Assessment at Work: Current Status and Future Challenges-A Systematic Review.
    Alberto R; Draicchio F; Varrecchia T; Silvetti A; Iavicoli S
    Int J Environ Res Public Health; 2018 Sep; 15(9):. PubMed ID: 30217079
    [No Abstract]   [Full Text] [Related]  

  • 20. Revised NIOSH lifting equation: a critical evaluation.
    Ahmad S; Muzammil M
    Int J Occup Saf Ergon; 2023 Mar; 29(1):358-365. PubMed ID: 35253606
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.