The action of lifting in humans is performed commonly, but can be affected by various factors. Examples of these factors include whether the person lifting has lower back pain, the kind of lift they are performing, how fatigued they are, or whether they are being externally assisted in the lifting motion. Since lifting is associated with increased rates of workplace injury, much work has been done to study the low-level impact that these elements can have, as well as how machine learning can help to detect and prevent them.
Factors affecting human lifting edit
Fatigue edit
At the muscular level, fatigue is the reduced ability of muscles to generate force. In strenuous tasks like lifting, this sort of shift in the body’s ability to move can create changes in muscle activation as well as overall motion.[1][2][3][4] Fatigue onset is typically related to repeated actions taken in the same manner over a long period. Once the muscles helping to perform the action are unable to provide the same level of assistance to the body, risk of injury can increase.
In lifting, fatigue can create differences in how people move. Previous work has included correlating perceived exertion during lifting with significant changes of lifting kinematics over time.[3] Fatigue onset has also been shown to occur more slowly when people change their lifting style over time, or at least switch up which muscle groups they use. This is an example of the repeaters-replacers hypothesis at work.[1]
Lower back pain edit
Lower back pain can be caused by various factors, meaning that roughly 80% of the population will experience it within their lifetime.[5] However, a large portion of this group stems from manual materials handling-related work.[6] Overextending oneself, lifting with bad form, or otherwise performing a strenuous motion unsafely can vastly increase the risk of injury when lifting. To better quantify these risk types, methods have been devised of classifying workplace-required lifting motions based on their risk type.
There are a variety of effects that lower back pain can have on the motion of lifting, ranging from kinematic changes (whole-body motion) to individual muscle-level shifts. Previous work has explored the different types of lifting styles that individuals with lower back pain use compared with healthy individuals,[2] as well as changes in their muscle activation.[7] An interesting trend in individuals with lower back pain is that many tend to prefer slower, more precise motions that they achieve by using muscles on the back and front of their bodies at the same time.[4] This technique can help them to avoid pain, but using a strategy that is stiffer and uses more muscles can also be more fatiguing and cause greater spinal compressive forces as a result.[6]
Other factors edit
The amount of perceived weight that an object has can also affect the way that someone lifts it. Researchers have shown that deceiving people into thinking that an object is heavier or lighter can change their perceived exertion after performing a series of lifts with it, as well as muscle activity. However, changes in back muscle activity are usually restricted to the phase of lifting before a person actually picks up an object. During the lifting phase itself, the weight of that object is the dominant factor affecting back muscle activity.[8]
Measuring lifting changes edit
To measure changes in lifting, there are a variety of data that researchers can collect. They include direct physiological measurements and subject-reported outcome measures. Some examples include:
- Motion capture
- Electromyography (EMG)
- Force plates
- Rating of perceived exertion[9]
- Pain self-efficacy[10]
One emerging area of research is the use of machine learning to detect changes in lifting from fatigue[3] or to distinguish different lifting styles due to the prevalence of lower back pain.[10] These methods are useful because they can allow clinicians to see shifts in lifting that might not be immediately distinguishable to the naked eye or raw sensor measurements.
References edit
- ^ a b Oomen, Nathalie M.C.W.; Graham, Ryan B.; Fischer, Steven L. (2023). "Exploring the relationship between kinematic variability and fatigue development during repetitive lifting". Applied Ergonomics. 107: 103922. doi:10.1016/j.apergo.2022.103922.
- ^ a b Kazemi, Zeinab; Mazloumi, Adel; Arjmand, Navid; Keihani, Ahmadreza; Karimi, Zanyar; Ghasemi, Mohamad Sadegh; Kordi, Ramin (2022). "A Comprehensive Evaluation of Spine Kinematics, Kinetics, and Trunk Muscle Activities During Fatigue-Induced Repetitive Lifting". Human Factors: The Journal of the Human Factors and Ergonomics Society. 64 (6): 997–1012. doi:10.1177/0018720820983621. ISSN 0018-7208.
- ^ a b c Hawley, Sheldon J.; Hamilton-Wright, Andrew; Fischer, Steven L. (2023-01-02). "Detecting subject-specific fatigue-related changes in lifting kinematics using a machine learning approach". Ergonomics. 66 (1): 113–124. doi:10.1080/00140139.2022.2061052. ISSN 0014-0139.
- ^ a b Varrecchia, Tiwana; Conforto, Silvia; De Nunzio, Alessandro Marco; Draicchio, Francesco; Falla, Deborah; Ranavolo, Alberto (2022-02-12). "Trunk Muscle Coactivation in People with and without Low Back Pain during Fatiguing Frequency-Dependent Lifting Activities". Sensors. 22 (4): 1417. doi:10.3390/s22041417. ISSN 1424-8220. PMC 8874369. PMID 35214319.
{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link) - ^ Waddell, Gordon (1987). "1987 Volvo Award in Clinical Sciences: A New Clinical Model for the Treatment of Low-Back Pain:". Spine. 12 (7): 632–644. doi:10.1097/00007632-198709000-00002. ISSN 0362-2436.
- ^ a b Marras, William S.; Lavender, Steven A.; Leurgans, Sue E.; Rajulu, Sudhakar L.; Allread, W Gary; Fathallah, Fadi A.; Ferguson, Sue A. (1993). "The Role of Dynamic Three-Dimensional Trunk Motion in Occupationally-Related Low Back Disorders". Spine. 18 (5): 617–628. doi:10.1097/00007632-199304000-00015. ISSN 0362-2436.
- ^ Larivière, Christian; Gagnon, Denis; Loisel, Patrick (2002). "A biomechanical comparison of lifting techniques between subjects with and without chronic low back pain during freestyle lifting and lowering tasks". Clinical Biomechanics. 17 (2): 89–98. doi:10.1016/S0268-0033(01)00106-1.
- ^ Courbalay, Anne; Tétreau, Charles; Lardon, Arnaud; Deroche, Thomas; Cantin, Vincent; Descarreaux, Martin (2017). "Contribution of Load Expectations to Neuromechanical Adaptations During a Freestyle Lifting Task: A Pilot Study". Journal of Manipulative and Physiological Therapeutics. 40 (8): 547–557. doi:10.1016/j.jmpt.2017.07.004.
- ^ "The Borg Rating of Perceived Exertion (RPE) scale". academic.oup.com. 1987. doi:10.1093/occmed/kqx063. Retrieved 2023.
{{cite web}}: Check date values in:|access-date=(help) - ^ a b Phan, Trung C.; Pranata, Adrian; Farragher, Joshua; Bryant, Adam; Nguyen, Hung T.; Chai, Rifai (2022-09-04). "Machine Learning Derived Lifting Techniques and Pain Self-Efficacy in People with Chronic Low Back Pain". Sensors. 22 (17): 6694. doi:10.3390/s22176694. ISSN 1424-8220. PMC 9460822. PMID 36081153.
{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
External links edit