Methods for clinical evaluation

This chapter begins with an introduction to the challenges of measurement in upper limb prosthetics. This is followed by an overview of the traditional approaches to evaluation and their strengths and weaknesses. By traditional approaches, we mean tests involving observation of a participant performing a structured activity or reporting on their everyday experiences and behaviours through questionnaires. These approaches generally involve little, if any, instrumentation and are still widely used. In the next section, we report on the evaluation tools which have emerged from studies of human motor control; these include observation of the kinematics during the performance of tasks and measures which may reflect attentional demands, such as gaze behaviours and brain activity. As the so-called conventional methods and the human-motor-control-based methods either observe behaviours over a short period of time or ask people to accurately recall and report on their behaviours, both have inherent limitations. Finally, we report on methods which can be used to capture, in detail, the everyday upper limb behaviours of people in the real world and discuss the opportunities such real-world approaches open up around data analysis at scale. Chapter Contents: • 3.1 Measurement issues in upper limb prosthetics • 3.2 Traditional methods • 3.2.1 Questionnaires - participation domain • 3.2.2 Observational measures - activity domain • 3.2.2.1 Assessment of Capacity of Myoelectric Control • 3.2.3 Time-based outcome measures - activity domain • 3.2.3.1 The Southampton Hand Assessment Procedure • 3.2.4 Clinic-based activities • 3.2.4.1 Box and blocks • 3.2.4.2 Clothespin Relocation Task • 3.2.4.3 Activities measure for upper limb amputees • 3.3 Laboratory-based techniques • 3.3.1 Gaze behaviour • 3.3.2 Kinematics • 3.3.2.1 Measurement techniques • 3.3.2.2 Goal-directed movement in anatomically intact participants • 3.3.2.3 Kinematics of goal-directed movement in prosthesis users • 3.3.2.4 Motion capture combined with existing tests • 3.3.2.5 Kinematic variability • 3.3.2.6 Workspace • 3.3.2.7 Other approaches (gesture intensity/frequency) • 3.3.3 Eye-tracking and EEG • 3.3.4 Discussion • 3.4 Real-world techniques • 3.4.1 Real-world monitoring • 3.4.2 Real-world assessment of upper limb activity • 3.4.2.1 Non-wear algorithms • 3.4.2.2 Metrics to capture prosthesis use • 3.4.3 Discussion • 3.5 Data science, big data, standards and the future • 3.5.1 Small-scale, short-term studies • 3.5.2 Study bias • 3.5.3 Absence of useful data on prostheses characteristics and lack of standardisation on participant characteristics • 3.5.4 Limited adoption of standard approaches to measuring outcomes • 3.5.5 Data science and big data • 3.6 Discussion and conclusions • Acknowledgements • References