Using Electroencephalography (EEG) Power Responses to Investigate the Effects of Ambient Oxygen Content, Safety Shoe Type, and Lifting Frequency on the Worker’s Activities

• Published in: BioMed research international 2020, Vol.2020 (2020), p.1-13
• Main Authors: Ramadan, Mohamed Z., Ragab, Adham Ezzat, Ghaleb, Atef M.
• Format: Article
• Language: English
• Subjects: Acclimatization; Adult; Airports; Algorithms; Analysis; Blood Gas Analysis - methods; Brain research; Construction materials; Dependent variables; EEG; Electroencephalography; Electroencephalography - methods; Farms; Fatigue; Health risks; Heart rate; High-altitude environments; Hoisting; Hospitals; Human performance; Humans; Hypoxia; Independent variables; Industrial plants; Industrial safety; Investigations; Levels; Lifting; Male; Materials handling; Metabolism; Occupational health; Oxygen; Oxygen - analysis; Oxygen content; Packaging; Physiology; Power spectral density; Protective equipment; Psychophysics - methods; Replication; Safety; Shoes; Shoes & boots; Studies; Ventilation; Warehouses
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2020/7956037

Objective. The study assesses the changes in electroencephalography (EEG) power spectral density of individuals in hypoxia when wearing a different type of safety shoes under different lifting frequencies. It also assesses the EEG response behavior induced via the process of lifting loads related to these variables. Methods. The study was conducted in two consecutive phases: training and acclimatization phase and experimental lifting phase. Ten male college students participated in this study. A four-way repeated measures design was used in this research with independent variables: ambient oxygen content (“15%, 18%, and 20%”), safety shoes type (“light-duty, medium-duty, and heavy-duty”), lifting frequency (“1 and 4 lifts/min”), and replication (“first and second”). And the dependent variables were alpha, theta, beta, gamma, θ/α, θ/β, α/β, β/α, (θ+α)/β, and (θ+α)/(α+β). The participant was allowed to determine his maximum acceptable weight of lift (MAWL) in fifteen minutes of lifting using psychophysically technique. Then, he continued lifting the MAWL for another five minutes, where all the data were collected. Results. Results showed that the EEG responses at lower levels of the independent variables were significantly high than at higher levels; except for oxygen content, the EEG responses at lower levels were considerably lower than at a higher level. It also showed that an upsurge in the physical demand increased lifting frequency and replication and caused decreasing in alpha power, theta/beta, alpha/beta, (theta+alpha)/beta, (theta+alpha)/(alpha+beta) and increasing in the theta power and the gamma power. Furthermore, several interactions among independent variables had significant effects on the EEG responses. Conclusion. The EEG implementation for the investigation of neural responses to physical demands allows for the possibility of newer nontraditional and faster methods of human performance monitoring. These methods provide effective and reliable results as compared to other traditional methods. This study will safeguard the physical capabilities and possible health risks of industrial workers. And the applications of these tasks can occur in almost all working environments (factories, warehouses, airports, building sites, farms, hospitals, offices, etc.) that are at high altitudes. It can include lifting boxes at a packaging line, handling construction materials, handling patients in hospitals, and cleaning.