Children's Postures While Playing at Computer Workstations

There has been a significant increase in the incidence of musculoskeletal disorders (MSD) and the costs associated with these are predicted to increase as the popularity of computer use increases at home, school and work. Risk factors have been identified in the adult population but little is known about the risk factors for children and youth. Research has demonstrated that they are not immune to this risk and that they are self reporting the same pain as adults. The purpose of the study was to examine children’s postures while working at computer workstations under two conditions. One was at an ergonomically adjusted children’s workstation while the second was at an average adult workstation. A Polhemus Fastrak™ system was used to record the children’s postures and joint and segment angles were quantified. Results of the study showed that children reported more discomfort and effort at the adult workstation. Segment and joint angles showed significant differences through the upper limb at the adult workstation. Of significance was the strategy of shoulder abduction and flexion that the children used in order to place their hand on the mouse. Ulnar deviation was also greater at the adult workstation as was neck extension. All of these factors have been identified in the literature as increasing the risk for injury. A comparison of the children’s posture while playing at the children’s workstation verses the adult workstation, showed that the postural angles assumed by the children at an adult workstation exceeded the Occupational Safety and Health Association (OSHA) recommendations. Further investigation is needed to increase our knowledge of MSD in children as their potential for long term damage has yet to be determined.

THE DESIGN OF A POWER SYSTEM FOR A WIRELESS SENSOR NETWORK FOR LONG-TERM OPERATION

Wireless sensor networks (WSNs) have shown wide applicability to many fields including monitoring of environmental, civil, and industrial settings. WSNs however are resource constrained by many competing factors that span their hardware, software, and networking. One of the central resource constrains is the charge consumption of WSN nodes. With finite energy supplies, low charge consumption is needed to ensure long lifetimes and success of WSNs. This thesis details the design of a power system to support long-term operation of WSNs. The power system’s development occurs in parallel with a custom WSN from the Queen’s MEMS Lab (QML-WSN), with the goal of supporting a 1+ year lifetime without sacrificing functionality. The final power system design utilizes a TPS62740 DC-DC converter with AA alkaline batteries to efficiently supply the nodes while providing battery monitoring functionality and an expansion slot for future development. Testing tools for measuring current draw and charge consumption were created along with analysis and processing software. Through their use charge consumption of the power system was drastically lowered and issues in QML-WSN were identified and resolved including the proper shutdown of accelerometers, and incorrect microcontroller unit (MCU) power pin connection. Controlled current profiling revealed unexpected behaviour of nodes and detailed current-voltage relationships. These relationships were utilized with a lifetime projection model to estimate a lifetime between 521-551 days, depending on the mode of operation. The power system and QML-WSN were tested over a long term trial lasting 272+ days in an industrial testbed to monitor an air compressor pump. Environmental factors were found to influence the behaviour of nodes leading to increased charge consumption, while a node in an office setting was still operating at the conclusion of the trail. This agrees with the lifetime projection and gives a strong indication that a 1+ year lifetime is achievable. Additionally, a light-weight charge consumption model was developed which allows charge consumption information of nodes in a distributed WSN to be monitored. This model was tested in a laboratory setting demonstrating +95% accuracy for high packet reception rate WSNs across varying data rates, battery supply capacities, and runtimes up to full battery depletion.