ABSTRACT
Recognizing pain in people with communicative disabilities is challenging. A support system detecting pain signals provides caregivers with information to intervene adequately. This study aims to develop a design for a user interface visualizing pain experiences for a signalling system intended for caregivers. Caregivers receive alerts, indicating the presence or absence of pain experienced by a disabled individual. The design process included the use of value proposition, a brainstorm, a mood board with basic design elements, and multiple questionnaires and focus groups. During the multi-disciplinary design process end-users were extensively involved. The final design was deemed intuitive, clear and recognizable, and useable in daily caregiving. This article describes the creation process for a non-hedonistic visualization for this niche end-user group.
ABSTRACT
Results: The methods' heart rate variability and electroencephalogram show clear and consistent results as acute pain assessment. Magnetic resonance imaging can measure chronic pain. Ordered by invasiveness and vulnerability, a trend shows that the invasive methods are used more with less vulnerable subjects. Only instruments used for skin conductance and automatic facial recognition have a lower-than-average technological maturity. Conclusions: Some pain assessment methods show good and consistent results and have high technological maturity; however, using them as pain assessment for persons with ID is uncommon. Since this addition can ameliorate caregiving, more research of assessment methods should occur.
Subject(s)
Acute Pain/diagnosis , Chronic Pain/diagnosis , Pain Measurement/methods , Female , HumansABSTRACT
Successful results have been booked with using robotics in therapy interventions for autism spectrum disorders (ASD). However, to make the best use of robots, the behavior of the robot needs to be tailored to the learning objectives and personal characteristics of each unique individual with ASD. Currently training practices include adaptation of the training programs to the condition of each individual client, based on the particular learning goals or the mood of the client. To include robots in such training will imply that the trainers are enabled to control a robot through an intuitive interface. For this purpose we use a visual programming environment called TiViPE as an interface between robot and trainer, where scenarios for specific learning objectives can easily be put together as if they were graphical LEGO-like building blocks. This programming platform is linked to the NAO robot from Aldebaran Robotics. A process flow for converting trainers' scenarios was developed to make sure the gist of the original scenarios was kept intact. We give an example of how a scenario is processed, and implemented into the clinical setting, and how detailed parts of a scenario can be developed.
Subject(s)
Child Development Disorders, Pervasive/therapy , Robotics/instrumentation , Robotics/methods , Child , Child, Preschool , Humans , Robotics/education , Software , User-Computer InterfaceABSTRACT
When designing an ECG monitoring system embedded with textile electrodes for comfort, it is challenging to ensure reliable monitoring, because textile electrodes suffer from motion artifacts and incidental poor signal quality. For the design of a comfortable monitoring system for prematurely born babies in the Neonatal Intensive Care Unit (NICU), we propose the concepts of 'diversity measurement' and 'context awareness' to improve reliability. Clinical multi-modal sensor data was collected in the NICU with the Smart Jacket connected to a state-of-the-art amplifier. We found that the ECG signals quality varied among sensors and varied over time, and found correlations between ECG signal, acceleration data, and context, which supports the feasibility of the concepts. Our explorative system level approach has lead to design parameters and meta-insights into the role of clinical validation in the design process.
