The aim of the study reported here was to reflect and report on lessons learned from adapting HCI methods to fit into an agile development process delivering a digital intervention for people managing Long Covid. During the project, we maintained a record of all activities and interim design products. Subsequently, selected records were analysed qualitatively. Challenges included engaging patients managing this complex, debilitating health condition and fitting the digital intervention into different and evolving patient pathways provided by clinics. The key contributions of this paper are a description of the clinically supported self-management app, Living With Covid Recovery, and of adapted methods for user-centred design and testing; narratives on engaging diverse clinics integrating a digital health intervention in their care pathways; reflections on designing for diverse users; implications for design of future technologies for supported self-management; and insights into multidisciplinary working that are rarely discussed within HCI.

Our goal is to develop an automated assessment and training procedure for children with eye-hand coordination problem. An automated assessment system is expected to reduce the burden and the associated cost of having a trained professional present at any assessment, or training session. The intelligent decision support system will be based upon a fuzzy automaton. By using qualitative (fuzzified) data from the previous test the system will make a decision on the complexity of the next test to be performed. A set of assessment tests, commonly used by occupational therapists, were chosen to implement the various functions using force, inertia and viscosity effects. A test bed will be used for these tasks that consists of a six-degree-of-freedom force-reflecting haptic interface device called PHANToM along with the GHOST SDK Software, and the Intelligent Decision Support System software

We discuss the possibility of improving eyehand coordination in children diagnosed with this problem, using a robotic mapping from a haptic user interface to a virtual environment. Our goal is to develop an assessment and training procedure that will result in improving handwriting taking the advantage of the force feedback provided by the haptic device. Force feedback can be used to guide the subject's hand in a predetermined trajectory when he/she is unable to move in response to visual feedback. We also incorporate the inertia and viscosity effects to decrease the tremor in the hand as well as to stimulate the muscles involved in the task of holding a pencil (known as facilitation technique in the occupational therapy field). The robotic system is operated within ranges established by baseline data for accuracy of eye-hand coordination and grip strength. A set of assessment tests, commonly used by occupational therapists, were chosen to implement the various functions using force, inertia and viscosity effects. The test bed used for these tasks consisted of a six-degree-of-freedom force reflecting haptic interface device, PHANToM with the GHOST SDK Software. Preliminary data obtained from two children diagnosed with eye-hand coordination problems show that the assistance provided, improved their ability to execute and complete the tasks, suggesting that the system could be used for assessment and training purposes. In addition, these results suggest that the introduction of the haptic rendering capabilities, including the force feedback, offers special benefit and measures the impact on the occupation of handwriting. Furthermore, a real application of this system could be implemented in the future, by identifying specific job tasks that may be made accessible through a desktop in classrooms by the aforementioned haptic system.