LifeChair: A Conductive Fabric Sensor-Based Smart Cushion for Actively Shaping Sitting Posture.

The LifeChair is a smart cushion that provides vibrotactile feedback by actively sensing and classifying sitting postures to encourage upright posture and reduce slouching. The key component of the LifeChair is our novel conductive fabric pressure sensing array. Fabric sensors have been explored in the past, but a full sensing solution for embedded real world use has not been proposed. We have designed our system with commercial use in mind, and as a result, it has a high focus on manufacturability, cost-effectiveness and adaptiveness. We demonstrate the performance of our fabric sensing system by installing it into the LifeChair and comparing its posture detection accuracy with our previous study that implemented a conventional flexible printed PCB-sensing system. In this study, it is shown that the LifeChair can detect all 11 postures across 20 participants with an improved average accuracy of 98.1%, and it demonstrates significantly lower variance when interfacing with different users. We also conduct a performance study with 10 participants to evaluate the effectiveness of the LifeChair device in improving upright posture and reducing slouching. Our performance study demonstrates that the LifeChair is effective in encouraging users to sit upright with an increase of 68.1% in time spent seated upright when vibrotactile feedback is activated

An experimental approach for the characterization of prolonged sitting postures using pressure sensitive mats

The adoption of prolonged sitting posture,which is a condition commonly encountered in several working tasks,is known to induce a wide range of negative effects,including discomfort,which has been recognized as an early predictor for musculoskeletal disorders (particularly low back pain).In this regard,the continuous monitoring of worker’s psychophysical state while sitting for long periods of time, may result useful in to preventing and managing potentially risky situations and to promote ergonomics and macroergonomics interventions,aimed to better organize work shifts and workplaces.The aim of this dissertation is to provide and test the reliability of a set of monitoring parameters,based on the use of quantitative information derived from body-seat contact pressure sensors.In particular, he study was focused on the assessment of trunk postural sway (the small oscillations resulting from the stabilization control system) and the number of In Chair Movements (ICM) or postural shifts performed while sitting, proven as a reliable tool for discomfort prediction. This thesis is articulated into four experimental campaigns.The first is a pilot study which aimed to define the most reliable algorithm and the set of parameters useful to assess the performed postural shifts or In chair Movements (ICM), which result useful to characterize postural strategies in the long term-monitoring. In this regard, a pilot study was conducted in which two different algorithms for the ICM computing were tested, based on different parameters and having different thresholds. The chosen algorithm was used, together with trunk sway parameters, to evaluate postural strategies in the other three experiments of this thesis. The second and the third studies evaluated sitting postural strategies among bus drivers during regular, long-term work shifts performed on urban and extra-urban routes. The results, in this case, showed that, all drivers reported a constant increase in perceived discomfort levels and a correspondent increase in trunk sway and overall number of ICM performed. This may indicate the adoption of specific strategies in order to cope with discomfort onset, a fatigue-induced alteration of postural features, or both simultaneously. However, it was interesting to observe differences in ICM vs trunk sway trend considering the single point-to-point route in the case of urban drivers. This difference between may indicate that these parameters refer to different aspects of sitting postural strategies: ICM may be more related to discomfort while sway may be more representative of task-induced fatigue. Trunk sway monitoring, as well as the count of ICM performed by bus drivers may thus be a useful tool in detecting postural behaviors potentially associated with deteriorating performance and onset of discomfort. Finally, the last experiment aimed to characterize modifications in sitting behavior, in terms of trunk sway and ICM among office workers during actual shifts. Surprisingly, results showed a decreasing trend in trunk sway parameters and ICM performed over time, with significant modifications in sitting posture in terms of trunk flexion-extension. Subjects were also stratified basing on their working behavior (staying seated or making short breaks during the trial) and significant differences were identified among these two groups in terms of postural sway and perceived discomfort. This may indicate that the adoption of specific working strategies can significantly influence sitting behavior and discomfort onset. In conclusion, the trunk sway monitoring and the ICM assessment in actual working environments may represent a useful tool to detect specific postural behaviors potentially associated with deteriorating performance and onset of discomfort, both among professional drivers and office workers.They might effectively support the evaluation of specific working strategies,as well as the set-up of macroergonomics interventions

Novel sedentary behaviour measurement methods: application for self-monitoring in adults

With the introduction of the technological age, increasing mechanisation has led to labour saving devices which have all-but engineered physical activity out of our lives and sedentary behaviour has now become the default behaviour during waking hours. Interventions that previously focused on improving levels of physical activity are now attempting to concurrently increase levels of physical activity and decrease time spent in sedentary behaviour. One method that has shown promise in interventions to increase physical activity and healthy eating in adults is the behaviour change technique of self-monitoring. There is now a robust set of literature indicating self-monitoring as the most promising behaviour change technique in this area. Self-monitoring is tied inherently into the recent rise in wearable technology. These new devices have the ability to track a variety of behavioural and physiological parameters and immediately make the information returnable to the user via connected mobile applications. The potential pervasive nature of these technologies and their use of robust behaviour change techniques could make them a useful tool in interventions to reduce sedentary behaviour. Therefore the overall purpose of this three study dissertation was to identify and validate technology that can self-monitor sedentary behaviour and to determine its feasibility in reducing sedentary behaviour. Study 1 Purpose: The aim of this study was to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary behaviour and/or physical activity. Methods: To identify technologies, four scientific databases were systematically searched using key terms related to behaviour, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1st, 2015. Results: The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored physical activity, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring physical activity and/or sedentary behaviour; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on physical activity (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary behaviour (activPAL VT, the LumoBack, and Darma). Conclusions: There are a large number of devices that self-monitor physical activity; however, there is a greater need for the development of tools to self-monitor sedentary time. The novelty of these devices means they have yet to be used in behaviour change interventions, although the growing field of wearable technology may facilitate this to change. Study 2 Purpose: The aim of this study was to examine the criterion and convergent validity of the LumoBack as a measure of sedentary behaviour compared to direct observation, the ActiGraph wGT3X+ and the activPAL under laboratory and free-living conditions in a sample of healthy adults. Methods: In the laboratory experiment, 34 participants wore a LumoBack, ActiGraph and activPAL monitor and were put through seven different sitting conditions. In the free-living experiment, a sub-sample of 12 participants wore the LumoBack, ActiGraph and activPAL monitor for seven days. Validity were assessed using Bland-Altman plots, mean absolute percentage error (MAPE), and intraclass correlation coefficient (ICC). T-test and Repeated Measures Analysis of Variance were also used to determine any significant difference in measured behaviours. Results: In the laboratory setting, the LumoBack had a mean bias of 76.2, 72.1 and -92.3 seconds when compared to direct observation, ActiGraph and activPAL, respectively, whilst MAPE was less than 4%. Furthermore, the ICC was 0.82 compared to the ActiGraph and 0.73 compared to the activPAL. In the free-living experiment, mean bias was -4.64, 8.90 and 2.34 seconds when compared to the activPAL for sedentary behaviour, standing time and stepping time respectively. Mean bias was -38.44 minutes when compared to the ActiGraph for sedentary time. MAPE for all behaviours were 0.75. Conclusion: The LumoBack has acceptable validity and reliability as a measure of sedentary behaviour. Study 3 Purpose: The aim of this study was to explore the use of the LumoBack as a behaviour change tool to reduce sedentary behaviour in adults. Methods: Forty-two participants (≥25 years) who had an iPhone 4S or later model wore the LumoBack without any feedback for one week for baseline measures of behaviour. Participants then wore the LumoBack for a further five weeks whilst receiving feedback on sedentary behaviour via a sedentary vibration from the device and feedback on the mobile application. Sedentary behaviour, standing time, and stepping time were objectively assessed using the LumoBack. Differences in behaviour were determined between baseline, week 1 and week 5. Participant engagement with the LumoBack was determined using Mobile app analytics software. Results: There were no statistically significant differences in behaviour between baseline and the LumoBack intervention period (p>0.05). Participants engaged most with the Steps card on the LumoBack app with peaks in engagement seen at week 5. Conclusion: This study indicates that using the LumoBack on its own was not effective in reducing sedentary behaviour in adults. Self-monitoring and feedback may need to be combined with other behaviour change strategies such as environmental restructuring to be effective. General Conclusion This thesis found that there are currently an abundance of technologies which self-monitors physical activity but a lack of devices which measuring sedentary behaviour. One such device, the LumoBack, has shown to have acceptable validity as a measure of sedentary behaviour. Whilst the use of the LumoBack as a behaviour change tool did not elicit any significant changes, its ability to be a pervasive behavioural intervention and the use of user-defined nudging can make the LumoBack, and other similar low cost, valid objective sedentary behaviour self-monitors key components in multi-faceted interventions

A Work Injury Prevention Program for a Rural Manufacturing Company

Purpose: This article discusses how a group of four physical therapy students built upon traditional ergonomic and biomechanical programs and applied it to a rural manufacturing company of 160 employees. Methods: Meetings were held with the corporation\u27s Safety Specialist and upper management. Based on research supported by evidence and suggestions from the company\u27s administration, the students constructed an injury prevention program consisting of two presentations for office and production workers, exercise programs, a lifting and posture DVD and assessment, and a modified office assessment. Results: Seventy-one employees attended the production lecture. Thirty-six workers took part in the office presentation. Sixty-four production individuals took part in the posture and lifting screen. Thirty-three employees demonstrated a decreased forward head, twenty-two brought their shoulders back, and twenty-four corrected excessive pelvic tilts post lecture. Seventeen individuals didn\u27t change their posture. Post lecture all individuals bent their knees correctly and 56 brought the box close enough to lift the box properly. Only one person twisted his/her back post lecture to move the box. Twelve worker\u27s offices were evaluated after the office lecture. Some of the common problems were fixed during the assessment. Recommendations were made for different equipment or equipment modification. These modification changes are the responsibility of the company. Discussion: Although, improvements were made initially with both the office workers in their desk set-up arid the production with standing posture and lifting techniques, a long term follow-up needs to be done to assess the retention rates among the employees. This program provides a plan of what could to be done initially to produce an evidence-based injury prevention program within a manufacturing company