Prolonged static sitting at the workplace is considered one of the main risks for the development of musculoskeletal disorders (MSDs) and adverse health effects. Factors such as poor posture and extended sitting are perceived to be a reason for conditions such as lumbar discomfort and lower back pain (LBP), even though the scientific explanation of this relationship is still unclear and raises disputes in the scientific community. The current study focused on evaluating the relationship between LBP and prolonged sitting in poor posture using photogrammetric images, postural angle calculation, machine learning models, and questionnaire-based self-reports regarding the occurrence of LBP and similar symptoms among the participants. Machine learning models trained with this data are employed to recognize poor body postures. Two scenarios have been elaborated for modeling purposes: scenario 1, based on natural body posture tagged as correct and incorrect, and scenario 2, based on incorrect body postures, corrected additionally by the rehabilitator. The achieved accuracies of respectively 75.3% and 85% for both scenarios reveal the potential for future research in enhancing awareness and actively managing posture-related issues that elevate the likelihood of developing lower back pain symptoms.

Work-related musculoskeletal disorders (WMSDs) are a significant public health concern, particularly in professions requiring prolonged static postures. Objectives: This study examined the influence of demographic and occupational factors on the WMSD prevalence and provides evidence-based recommendations for workplace health improvements. Methods: A cross-sectional study (July–September 2024) surveyed 80 office employees in Varna, Bulgaria, using the Prevent 4 Work (P4Wq) questionnaire. ANOVA and t-tests assessed the WMSD prevalence across demographics, while Pearson’s correlations examined associations with age, BMI, and work experience. Data were analyzed in Jamovi v.2.6 (p < 0.05). Results: The sample (92.5% women, mean age 47.2 years) reported a high WMSD prevalence, with cervical pain (88.8%), lower back pain (83.8%), and shoulder pain (75.0%) being the most common. Work experience, age, and BMI were significantly correlated with WMSD severity, while gender showed no significant associations. Conclusions: WMSDs are highly prevalent among office employees, with lower back, neck, and shoulder pain being the most common complaints. Factors such as higher BMI, longer work experience, and increased workload are associated with greater symptom severity. These results emphasize the urgent need for targeted workplace interventions aimed at reducing ergonomic risks, improving posture, and enhancing employee well-being, ultimately fostering a healthier and more productive work environment.

Improper sitting positions are known as the primary reason for back pain and the emergence of musculoskeletal disorders (MSDs) among individuals who spend prolonged time working with computer screens, keyboards, and mice. At the same time, it is well understood that automated technological tools can play an important role in the process of unhealthy habit alteration, so plenty of research efforts are focused on research and technology development (RTD) activities that aim to provide support for the prevention of back pain or the development of MSDs. Here, we report on creating a new resource in support of RTD activities aiming at the automated detection of improper sitting positions. It consists of multimodal multisensory recordings of 100 persons, made with a video recorder, camera, and wrist-attached sensors that capture physiological signals (PPG, EDA, skin temperature), as well as motion sensors (three-axis accelerometer). Our multimodal multisensory dataset (MMD-MSD) opens new opportunities for modeling the body stance (sitting posture and movements), physiological state (stress level, attention, emotional arousal and valence), and performance (success rate on the Stroop test) of people working with a computer. Finally, we demonstrate two use cases: improper neck posture detection from pictures, and task-specific cognitive load detection from physiological signals.

INTRODUCTION: Lately the polarized polychromatic non-coherent lower energy light emitted by the Bi­optron lamp has become more widely used in the physiotherapeutic practice. AIM: To study the effect of polarized polychromatic incoherent low energy light on pain, motor activity and quality of life in patients with vertebrogenic lower back pain and to compare it with other methods used in practice. MATERIALS AND METHODS: Object of the study were 60 patients with lower back pain. A control group (N=30, age 46±11.5 y.) was treated with basic therapy and the Bioptron apparatus. Functional tests of the motor activity (test of Thomayer and test of Schober), evaluation of the pain using visual analogue scale (VAS) evaluation of the quality of life using the Roland-Morris test in the beginning, at the end and 1 month after the treatment were used to evaluate the effectiveness of treatment. RESULTS: The results have a statistical significance of (p<0.05) for both groups regarding the reduction of the pain syndrome, the functional tests for mobility in the lumbar region and the quality of life. There’s also a statistical significance in comparing the results of the test group (TG) and the control group (CG) (p<0.05). CONCLUSION: Both methods reduced pain, improved the mobility of the lumbar region and improved the quality of life of patients with lower back pain. The complex methodology incorporating basic treatment with the use of polarized polychromatic non-coherent low energy light yielded better results than just ba­sic treatment.

Improper sitting positions are known as the primary reason for back pain and the emergence of musculoskeletal disorders (MSD) among individuals who spend prolonged time working with computer screens, keyboards, and mice. At the same time, it is well understood that automated technological tools can play an important role in the process of unhealthy habit alteration, so plenty of research efforts are focused on research and technology development (RTD) activities that aim to provide support to the prevention of back pain or the development of MSD. Here, we report on creating a new resource in support of RTD activities aiming at the automated detection of improper sitting positions. It consists of multimodal multisensory recordings of 100 persons made with a video recorder, camera, and wrist-attached sensors that capture physiological signals (PPG, EDA, Skin temperature), as well as motion sensors (three-axis accelerometer). Our multimodal multisensory dataset (MMD-MSD) opens new opportunities for modeling the body stance (sitting posture and movements), physiological state (stress level, attention, emotional arousal, valence), and performance (success rate on the Stroop test) of people working with a computer. Finally, we demonstrate two use cases: improper neck posture detection from pictures and cognitive load detection from physiological signals.

Physiological deformities of spine are formed during children growth and gradually build their posture, which is unstable throughout the entire preschool period. In recent years, there has been an increase in the number of spinal deformities. There are risk factors leading to spinal deformities that result from the modern lifestyle. It is characterised by reduced physical activity and lack of movement. This article provides a number of opportunities for children to spend a long time, using electronic devices from an early age. The time during which children sit at a chair in front of a desk in school and at home while preparing their homework and learning lessons increases. If the impact of non-ergonomic furniture in the learning environment on the pupils’ spine is added to the behaviour related to the lack of movement the trends toward increase in the number of spinal deformities among pupils may be considered as not accidental. It is appropriate to take preventive measures. There is a need to study and formulate ergonomic requirements for learning environment, as part of spinal deformities’ prevention.