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Background: Sedentary behavior (SB) is associated with several chronic diseases and office workers especially are at increased risk. SB is defined by a sitting or reclined body posture with an energy expenditure of ≤1.5 metabolic equivalents. However, current objective methods to measure SB are not consistent with its definition. There is no consensus on which sensor placement and type should be used. Aim: To compare the accuracy of newly developed artificial intelligence models for 15 sensor placements in combination with four signal types (accelerometer only/plus gyroscope and/or magnetometer) to detect posture and physical in-/activity during desk-based activities. Method: Signal features for the model development were extracted from sensor raw data of 30 office workers performing 10 desk-based tasks, each lasting 5 min. Direct observation (posture) and indirect calorimetry (in-/activity) served as the reference criteria. The best classification model for each sensor was identified and compared among the sensor placements, both using Friedman and post hoc Wilcoxon tests (p ≤ .05). Results: Posture was most accurately measured with a lower body sensor, while in-/activity was most accurately measured with an upper body or waist sensor. The inclusion of additional signal types improved the posture classification for some placements, while the acceleration signal already contained the relevant signal information for the in-/activity classification. Overall, the thigh accelerometer most accurately classified desk-based SB. Conclusion: This study favors, in line with previous work, the measurement of SB with a thigh-worn accelerometer and adds the information that this sensor is also accurate in measuring physical in-/activity while sitting and standing.

Background Sedentary Behaviour (SB) gets an increasing attention from ergonomics and public health due to its associated detrimental health effects. A large number of studies record SB with ActiGraph counts-per-minute cut-points, but we still lack valid information about what the cut-points tell us about office work. This study therefore analysed the concurrent and discriminant validity of commonly used cut-points to measure SB, activity level, and posture. Methods Thirty office workers completed four office tasks at three workplaces (conventional chair, activity-promoting chair, and standing desk) while wearing two ActiGraphs (waist and wrist). Indirect calorimetry and prescribed posture served as reference criteria. Generalized Estimation Equations analysed workplace and task effects on the activity level and counts-per-minute, and kappa statistics and ROC curves analysed the cut-point validity. Results The activity-promoting chair (p p = 1.0) increased the activity level, and both these workplaces increased the waist (p ≤ 0.003, ES ≥ 0.63) but not the wrist counts-per-minute (p = 0.74) compared to the conventional chair. The concurrent and discriminant validity was higher for activity level (kappa: 0.52–0.56 and 0.38–0.45, respectively) than for SB and posture (kappa ≤0.35 and ≤ 0.19, respectively). Furthermore, the discriminant validity for activity level was higher for task effects (kappa: 0.42–0.48) than for workplace effects (0.13–0.24). Conclusions ActiGraph counts-per-minute for waist and wrist placement were – independently of the chosen cut-point – a measure for activity level and not for SB or posture, and the cut-points performed better to detect task effects than workplace effects. Waist cut-points were most valid to measure the activity level in conventional seated office work, but they showed severe limitations for sit-stand desks. None of the placements was valid to detect the increased activity on the activity-promoting chair. Caution should therefore be paid when analysing the effect of workplace interventions on activity level with ActiGraph waist and wrist cut-points.

Background The Critical Shoulder Angle was introduced as a combined radiographic surrogate parameter reflecting the influence of the morphological characteristics of the scapula on the development of degenerative shoulder disease such as rotator cuff tears and osteoarthritis. Although, glenoid inclination and lateral extension of the acromion were studied in biomechanical models separately, no investigation included all three individual parameters that determine the Critical Shoulder Angle: glenoid inclination, acromial coverage and acromial height in one cadaveric study protocol. Methods Three proximal humerus cadavers were attached to a robotic shoulder simulator which allowed for independent change of either lateral acromial coverage, glenoid inclination or acromial height. Combined dynamic scapula-thoracic and glenohumeral abduction up to 60° with different Critical Shoulder Angle configurations was performed and muscle forces as well as joint reaction forces were recorded. Findings All three components had an effect on either muscle forces and or joint reaction forces. While glenoid inclination showed the highest impact on joint stability with increasing upward-tilting causing cranial subluxation, changing of the lateral acromial coverage or acromial height had less influence on stability but showed significant alteration of joint reaction forces. Interpretation All three components of the Critical Shoulder Angle, glenoid inclination, lateral acromial extension and acromial height showed independent biomechanical effects when changed isolated. However, glenoid inclination seems to have the largest impact regarding joint stability.

Background The critical shoulder angle combines the acromion index and glenoid inclination and has potential to discriminate between shoulders at risk for rotator cuff tear or osteoarthritis and those that are asymptomatic. However, its biomechanics, and particularly the role of the glenoid inclination, are not yet fully understood. Methods A shoulder simulator was used to analyze the independent influence of glenoid inclination during abduction from 0 to 60°. Spindle motors transferred tension forces by a cable-pulley on human cadaveric humeri. A six-degree-of-freedom force transducer was mounted directly behind the polyethylene glenoid to measure shear and compressive joint reaction force and calculate the instability ratio (ratio of shear and compressive joint reaction force) with the different force ratios of the deltoid and supraspinatus muscles (2:1 and 1:1). A stepwise change in the inclination by 5° increments allowed simulation of a critical shoulder angle range of 20° to 45°. Findings Tilting the glenoid to cranial (increasing the critical shoulder angle) increases the shear joint reaction force and therefore the instability ratio. A balanced force ratio (1:1) between the deltoid and the supraspinatus allowed larger critical shoulder angles before cranial subluxation occurred than did the deltoid-dominant ratio (2:1). Interpretation Glenoid inclination-dependent changes of the critical shoulder angle have a significant impact on superior glenohumeral joint stability. The increased compensatory activity of the rotator cuff to keep the humeral head centered may lead to mechanical overload and could explain the clinically observed association between large angles and degenerative rotator cuff tears.

Sedentary Behavior (SB) is among the most frequent human behaviors and is associated with a plethora of serious chronic lifestyle diseases as well as premature death. Office workers in particular are at an increased risk due to their extensive amounts of occupational SB. However, we still lack an objective method to measure SB consistent with its definition. We have therefore developed a new measurement system based on muscular activity and accelerometry. The primary aim of the present study was to calibrate the new-developed 8-CH-EMG+ for measuring occupational SB against an indirect calorimeter during typical desk-based office work activities. In total, 25 volunteers performed nine office tasks at three typical workplaces. Minute-by-minute posture and activity classification was performed using subsequent decision trees developed with artificial intelligence data processing techniques. The 8-CH-EMG+ successfully identified all sitting episodes (AUC = 1.0). Furthermore, depending on the number of electromyography channels included, the device has a sensitivity of 83&ndash, 98% and 74&ndash, 98% to detect SB and active sitting (AUC = 0.85&ndash, 0.91). The 8-CH-EMG+ advances the field of objective SB measurements by combining accelerometry with muscular activity. Future field studies should consider the use of EMG sensors to record SB in line with its definition.