Work-related musculoskeletal disorders are a major concern globally affecting societies, companies, and individuals. To address this, a new sensor-based system is presented: the Smart Workwear System, aimed at facilitating preventive measures by supporting risk assessments, work design, and work technique training. The system has a module-based platform that enables flexibility of sensor-type utilization, depending on the specific application. A module of the Smart Workwear System that utilizes haptic feedback for work technique training is further presented and evaluated in simulated mail sorting on sixteen novice participants for its potential to reduce adverse arm movements and postures in repetitive manual handling. Upper-arm postures were recorded, using an inertial measurement unit (IMU), perceived pain/discomfort with the Borg CR10-scale, and user experience with a semi-structured interview. This study shows that the use of haptic feedback for work technique training has the potential to significantly reduce the time in adverse upper-arm postures after short periods of training. The haptic feedback was experienced positive and usable by the participants and was effective in supporting learning of how to improve postures and movements. It is concluded that this type of sensorized system, using haptic feedback training, is promising for the future, especially when organizations are introducing newly employed staff, when teaching ergonomics to employees in physically demanding jobs, and when performing ergonomics interventions.

Vibrotactile feedback training may be one possible method for interventions that target at learning better work techniques and improving postures in manual handling. This study aimed to evaluate the short term effect of real-time vibrotactile feedback on postural exposure using a smart workwear system for work postures intervention in simulated industrial order picking. Fifteen workers at an industrial manufacturing plant performed order-picking tasks, in which the vibrotactile feedback was used for postural training at work. The system recorded the trunk and upper arm postures. Questionnaires and semi-structured interviews were conducted about the users’ experience of the system. The results showed reduced time in trunk inclination ≥20°, ≥30° and ≥45° and dominant upper arm elevation ≥30° and ≥45° when the workers received feedback, and for trunk inclination ≥20°, ≥30° and ≥45° and dominant upper arm elevation ≥30°, after feedback withdrawal. The workers perceived the system as useable, comfortable, and supportive for learning. The system has the potential of contributing to improved postures in order picking through an automated short-term training program.

Work metabolism (WM) can be accurately estimated by oxygen consumption (VO2), which is commonly assessed by heart rate (HR) in field studies. However, the VO2–HR relationship is influenced by individual capacity and activity characteristics. The purpose of this study was to evaluate three models for estimating WM compared with indirect calorimetry, during simulated work activities. The techniques were: the HR-Flex model; HR branched model, combining HR with hip-worn accelerometers (ACC); and HR + arm-leg ACC model, combining HR with wrist- and thigh-worn ACC. Twelve participants performed five simulated work activities and three submaximal tests. The HR + arm-leg ACC model had the overall best performance with limits of agreement (LoA) of −3.94 and 2.00 mL/min/kg, while the HR-Flex model had −5.01 and 5.36 mL/min/kg and the branched model, −6.71 and 1.52 mL/min/kg. In conclusion, the HR + arm-leg ACC model should, when feasible, be preferred in wearable systems for WM estimation.

In their paper, Andriessen at al present a validation of fetal ECG analysis and the clinical STAN device in midgestation fetal lambs exposed to 25 minutes of umbilical cord occlusion. The study presents results that contrast remarkably from previously published experimental data which raises a number of questions and comments. The most striking finding of Andriessen et al is the recording of an extremely high number of alarms from the STAN equipment during control conditions when no alarms at all are expected. These patterns have never been seen, neither in the clinical situation nor in our own fetal sheep studies. The reason for this becomes apparent when their way of recording the FECG is scrutinized. In their assessment of STAN, Andriessen at al use an assumed negative aVF lead with the assumption that it will reflect the FECG in the same way as the unipolar scalp lead used clinically. The signal used for disqualification of STAN is itself not qualified to properly represent the fetal scalp lead signal that STAN is designed for. To question a proven technology is fully accepted but those attempting would be asked to argue along fully validated data and related analysis including questioning of their own data.

In this work, we want to introduce combined heart rate and respiration monitoring for more accurate energy expenditure tracking on free-living subjects. We have developed a wearable cardiorespiratory monitoring system with unobtrusive heart rate measurement and ventilation estimation function for this purpose. The system is based on a garment with integrated textile electrodes for one-lead electrocardiogram and impedance pneumography measurements. A pilot experiment has been performed to prove the concept and to evaluate the characteristics of heart rate and ventilation estimated by our system in relation to energy expenditure. In the experiment, ventilation shows a better linearity in relation to the energy expenditure at the low intensity region than heart rate. Based on these characteristics, a model combining heart rate and ventilation for energy expenditure estimation is proposed which shows a significantly lower estimation error than the heart rate only model.

IntroductionFetal heart rate short term variation (STV) decreases with severe chronic hypoxia in the antenatal period. However, only limited research has been done on STV during labor. We have tested a novel algorithm for a valid baseline estimation and calculated STV. To explore the value of STV during labor, we compared STV with fetal scalp blood (FBS) lactate concentration, an early marker in the hypoxic process. Material and methodsSoftware was developed which estimates baseline frequency using a novel algorithm and thereby calculates STV according to Dawes and Redman in up to four 30-minute blocks prior to each FBS. Cardiotocography traces from 1070 women in labor who had had FBS performed on 2134 occasions were analyzed. ResultsIn acidemic cases (lactate >4.8mmol/L; Lactate Pro), median STV 30minutes prior to FBS was 7.10milliseconds compared with 6.09milliseconds in the preacidemic (4.2-4.8mmol/L) and 5.23milliseconds in the normal (<4.2mmol/L) groups (P<.05). There was a positive correlation between lactate and STV (rho=0.16-0.24; P<.05). Median lactate concentration in cases with STV <3.0milliseconds (n=160) was 2.3mmol/L. When 2 FBS were performed within 60minutes the change rate of lactate correlated to STV (rho=0.33; P<.001). Cases with increasing lactate concentration had a median STV of 5.29milliseconds vs 4.41milliseconds in those with decreasing lactate (P<.001). ConclusionsIn the early stages of intrapartum hypoxia, STV increases, contrary to findings regarding chronic hypoxia in the antenatal period. The increase in the adrenergic surge is a likely explanation.

Introduction.Reliability in visual cardiotocography interpretation isunsatisfying, which has led to the development of computerizedcardiotocography. Computerized analysis is well established for antenatal fetalsurveillance but has yet not performed sufficiently during labor. We aimed toinvestigate the capacity of a new computerized algorithm compared with visualassessment in identifying intrapartum fetal heart rate baseline anddecelerations.Material and methods.In all, 312 intrapartum cardiotocographytracings with variable decelerations were analyzed by the computerizedalgorithm and visually examined by two observers, blinded to each other andthe computer analysis. The width, depth and area of each deceleration wasmeasured. Four cases (>100 variable decelerations) were subjected to in-depthdetailed analysis. The outcome measures were bias in seconds (width), beatsper minute (depth), and beats (area) between computer and observers usingBland–Altman analysis. Interobserver reliability was determined by calculatingintraclass correlation and Spearman rank analysis.Results.The analysis (312cases) showed excellent intraclass correlation (0.89–0.95) and very strongSpearman correlation (0.82–0.91). The detailed analysis of>100 decelerationsin four cases revealed low bias between the computer and the two observers;width 1.4 and 1.4 seconds, depth 5.1 and 0.7 beats per minute, and area 0.1and–1.7 beats. This was comparable to the bias between the two observers:0.3 seconds (width), 4.4 beats per minute (depth) and 1.7 beats (area). Theintraclass correlation was excellent (0.90–.98).Conclusion.A novelcomputerized algorithm for intrapartum cardiotocography analysis is asaccurate as gold standard visual assessment, with high correlation and low bias.