Changes in working styles and physical activities, and an increase in psychological stress during the coronavirus disease 2019 (COVID-19) pandemic, may have affected pain conditions among workers with pain; however, these associations are still poorly understood. Therefore, we conducted a web-based, cross-sectional study to investigate these changes among Japanese workers suffering from pain. A total of 1941 workers who were aged 20–64 years and suffered from body pain within 4 weeks prior to the study were included. Information was collected using a self-reported questionnaire between July and August 2020. Among the respondents, 15% reported that their pain worsened during the COVID-19 pandemic. Approximately half of the workers claimed to have decreased physical activity (47%) and increased psychological stress (47%) during the pandemic. Multivariable logistic regression analyses found that telework (odds ratio 2.27, 95% confidence interval 1.68–3.06), decreased physical activity (3.18, 2.38–4.27), and increased psychological stress (2.16, 1.64–2.84) were associated significantly with pain augmentation. The group of workers who participated in telework and had decreased physical activity comprised the highest proportion of those with augmented pain. Our findings suggest that measures, which consider physical activities, psychological aspects, and working styles, to alleviate pain may be required for the working population in the future.

Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measures for absolute error and waveform pattern similarity in gait analysis using pose estimation AI (OpenPose). Additionally, we investigated the feasibility of simultaneous measuring both lower limbs using a single camera from one side. We compared motion analysis data from pose estimation AI using video footage that was synchronized with a three-dimensional motion analysis device. The comparisons involved mean absolute error (MAE) and the coefficient of multiple correlation (CMC) to compare the waveform pattern similarity. The MAE ranged from 2.3 to 3.1° on the camera side and from 3.1 to 4.1° on the opposite side, with slightly higher accuracy on the camera side. Moreover, the CMC ranged from 0.936 to 0.994 on the camera side and from 0.890 to 0.988 on the opposite side, indicating a “very good to excellent” waveform similarity. Gait analysis using a single camera revealed that the precision on both sides was sufficiently robust for clinical evaluation, while measurement accuracy was slightly superior on the camera side.

Anticipatory postural adjustments (APAs) provide postural stability and play an important role in ensuring appropriate motor performance. APAs also change in various situations. However, it is unknown whether changes in APAs during repetitive movement training contribute to improvement in motor performance. This study aimed to investigate the relationship between improvement in motor performance and changes in APAs during repeated reaching training, as well as the learning effects on APA changes. Sixteen healthy subjects (23 ± 2 years of age) stood barefoot on a force platform and reached as quickly and accurately as possible to a target placed at their maximum reach distance immediately following a beep signal in a reaction time condition. Whole-body reaching training with the right arm was repeated 100 times for three consecutive days. Motor performance and APAs were evaluated on the first day, after discontinuation of training for one day, and again at three months. In addition, reaching with the left arm (untrained limb) was tested on the first and the fifth training day. Body position segments were measured using three-dimensional motion analysis. Surface electromyography of eight postural muscles in both lower limbs was recorded. Kinetics data were recorded using the force platform. Whole-body reaching training induced not only improvements in motor performance (e.g., increased peak hand velocity), but also changes in APAs (e.g., earlier APA onset and increased amplitude). These changes were strongly correlated with and occurred earlier than improvements in motor performance. The learning effects on APAs were retained after the discontinuation of training and were generalized to the untrained limb. These results suggest that change in APAs contributes to improvement in motor performance; that is, the central nervous system may be able to adapt APAs for improvement in motor performance.

OpenPose-based motion analysis (OpenPose-MA), utilizing deep learning methods, has emerged as a compelling technique for estimating human motion. It addresses the drawbacks associated with conventional three-dimensional motion analysis (3D-MA) and human visual detection-based motion analysis (Human-MA), including costly equipment, time-consuming analysis, and restricted experimental settings. This study aims to assess the precision of OpenPose-MA in comparison to Human-MA, using 3D-MA as the reference standard. The study involved a cohort of 21 young and healthy adults. OpenPose-MA employed the OpenPose algorithm, a deep learning-based open-source two-dimensional (2D) pose estimation method. Human-MA was conducted by a skilled physiotherapist. The knee valgus angle during a drop vertical jump task was computed by OpenPose-MA and Human-MA using the same frontal-plane video image, with 3D-MA serving as the reference standard. Various metrics were utilized to assess the reproducibility, accuracy and similarity of the knee valgus angle between the different methods, including the intraclass correlation coefficient (ICC) (1, 3), mean absolute error (MAE), coefficient of multiple correlation (CMC) for waveform pattern similarity, and Pearson’s correlation coefficients (OpenPose-MA vs. 3D-MA, Human-MA vs. 3D-MA). Unpaired t-tests were conducted to compare MAEs and CMCs between OpenPose-MA and Human-MA. The ICCs (1,3) for OpenPose-MA, Human-MA, and 3D-MA demonstrated excellent reproducibility in the DVJ trial. No significant difference between OpenPose-MA and Human-MA was observed in terms of the MAEs (OpenPose: 2.4° [95%CI: 1.9-3.0°], Human: 3.2° [95%CI: 2.1-4.4°]) or CMCs (OpenPose: 0.83 [range: 0.99-0.53], Human: 0.87 [range: 0.24-0.98]) of knee valgus angles. The Pearson’s correlation coefficients of OpenPose-MA and Human-MA relative to that of 3D-MA were 0.97 and 0.98, respectively. This study demonstrated that OpenPose-MA achieved satisfactory reproducibility, accuracy and exhibited waveform similarity comparable to 3D-MA, similar to Human-MA. Both OpenPose-MA and Human-MA showed a strong correlation with 3D-MA in terms of knee valgus angle excursion.

The effects of changes in the anterior-posterior center of pressure (AP-COP) position on the lower limb joint moments during double-leg squatting remain unclear. The purpose of this study was to determine the effects of AP-COP positional changes on the hip, knee, and ankle extensor moments during double-leg squatting. Sixteen male participants (22.1 ± 1.5 years) performed double-leg squatting under two conditions (anterior and posterior COP conditions) with visual feedback on their COP positions. Kinematics and kinetics were analyzed using a three-dimensional motion analysis system and force plates. The hip, knee and ankle flexion angles and extensor moments at peak vertical ground reaction force were compared between the two conditions using paired t tests. The COP position was 53.5 ± 2.4% of the foot length, starting from the heel, under the anterior condition and 44.4 ± 2.1% under the posterior condition (P < 0.001). The knee extensor moment was significantly smaller under the anterior than the posterior COP condition (P = 0.003, 95% confidence interval (CI) -0.087 to -0.021 Nm/kg/m), while the ankle extensor moment significantly larger under the anterior COP condition than under the posterior COP condition (P < 0.001, 95% CI 0.113 to 0.147 Nm/kg/m). There was no significant difference in hip extensor moment (P = 0.431). The ankle dorsiflexion angle was significantly larger under the anterior than the posterior COP condition (P = 0.003, 95% CI 0.6 to 2.6°), while there was no difference in trunk, hip, or knee flexion angle. The present results indicate that changes in the AP-COP position mainly affect the ankle and knee extensor moments during double-leg squatting, while the effect on the lower limb joint and trunk flexion angles was limited. Visual feedback on the AP-COP position could be useful for modifying the ankle and knee extensor moments during double-leg squatting.