The meaning of environmental control systems (ECS) for people with spinal cord injury: An occupational therapist explores an intervention

Environmental Control Systems (ECS), enable people with high cervical Spinal Cord Injury (high SCI) to control and access everyday electronic devices. In Ireland, however, access for those who might benefit from ECS is limited. This study used a qualitative approach to explore the insider experience of an ECS starter-pack developed by the author, an occupational therapist. The primary research questions: what is it really like to live with ECS, and what does it mean to live with ECS, were explored using a phenomenological methodology conducted in three phases. In Phase 1 fifteen people with high SCI met twice in four focus groups to discuss experiences and expectations of ECS. Thematic analysis (Krueger & Casey, 2000), influenced by the psychological phenomenological approach (Creswell, 1998), yielded three categories of rich, practical, phenomenological findings: ECS Usage and utility; ECS Expectations and The meaning of living with ECS. Phase 1 findings informed Phase 2 which consisted of the development of a generic electronic assistive technology pack (GrEAT) that included commercially available constituents as well as short instructional videos and an information booklet. This second phase culminated in a one-person, three-week pilot trial. Phase 3 involved a six person, 8-week trial of the GrEAT, followed by individual in-depth interviews. Interpretative Phenomenological Analysis IPA (Smith, Larkin & Flowers, 2009), aided by computer software ATLAS.ti and iMindmap, guided data analysis and identification of themes. Getting used to ECS, experienced as both a hassle and engaging, resulted in participants being able to Take back a little of what you have lost, which involved both feeling enabled and reclaiming a little doing. The findings of this study provide substantial insights into what it is like to live with ECS and the meanings attributed to that experience. Several practical, real world implications are discussed.

The GrEAT pack: generic electronic assistive technology environmental control system - information booklet

This is a user manual for your electronic assistive technology environmental control system trial pack or in simple words – a few bits of technology that can let you control some household appliances. This information is intended for you, your family and carers.

Algorithms for indoor localization based on IEEE 802.15.4-2011 UWB and inertial sensors

In this thesis, extensive experiments are firstly conducted to characterize the performance of using the emerging IEEE 802.15.4-2011 ultra wideband (UWB) for indoor localization, and the results demonstrate the accuracy and precision of using time of arrival measurements for ranging applications. A multipath propagation controlling technique is synthesized which considers the relationship between transmit power, transmission range and signal-to-noise ratio. The methodology includes a novel bilateral transmitter output power control algorithm which is demonstrated to be able to stabilize the multipath channel, and enable sub 5cm instant ranging accuracy in line of sight conditions. A fully-coupled architecture is proposed for the localization system using a combination of IEEE 802.15.4-2011 UWB and inertial sensors. This architecture not only implements the position estimation of the object by fusing the UWB and inertial measurements, but enables the nodes in the localization network to mutually share positional and other useful information via the UWB channel. The hybrid system has been demonstrated to be capable of simultaneous local-positioning and remote-tracking of the mobile object. Three fusion algorithms for relative position estimation are proposed, including internal navigation system (INS), INS with UWB ranging correction, and orientation plus ranging. Experimental results show that the INS with UWB correction algorithm achieves an average position accuracy of 0.1883m, and gets 83% and 62% improvements on the accuracy of the INS (1.0994m) and the existing extended Kalman filter tracking algorithm (0.5m), respectively.