Quantitative Comparison of Human and Software Reliability in the Categorisation of Sit-to-stand Motion Pattern

The Sit-to-Stand (STS) test is used in clinical practice as an indicator of lower-limb functionality decline, especially for older adults. Due to its high variability, there is no standard approach for categorising the STS movement and recognising its motion pattern. This paper presents a comparative analysis between visual assessments and an automated-software for the categorisation of STS, relying on registrations from a force plate. 5 participants (30 +/- 6 years) took part in 2 different sessions of visual inspections on 200 STS movements under self-paced and controlled speed conditions. Assessors were asked to identify three specific STS events from the Ground Reaction Force, simultaneously with the software analysis: the start of the trunk movement (Initiation), the beginning of the stable upright stance (Standing) and the sitting movement (Sitting). The absolute agreement between the repeated raters' assessments as well as between the raters' and software's assessment in the first trial, were considered as indexes of human and software performance, respectively. No statistical differences between methods were found for the identification of the Initiation and the Sitting events at self-paced speed and for only the Sitting event at controlled speed. The estimated significant values of maximum discrepancy between visual and automated assessments were 0.200 [0.039; 0.361] s in unconstrained conditions and 0.340 [0.014; 0.666] s for standardised movements. The software assessments displayed an overall good agreement against visual evaluations of the Ground Reaction Force, relying, at the same time, on objective measures

Robustness and static-positional accuracy of the SteamVR 1.0 virtual reality tracking system

The use of low-cost immersive virtual reality systems is rapidly expanding. Several studies started to analyse the accuracy of virtual reality tracking systems, but they did not consider in depth the effects of external interferences in the working area. In line with that, this study aimed at exploring the static-positional accuracy and the robustness to occlusions inside the capture volume of the SteamVR (1.0) tracking system. To do so, we ran 3 different tests in which we acquired the position of HTC Vive PRO Trackers (2018 version) on specific points of a grid drawn on the floor, in regular tracking conditions and with partial and total occlusions. The tracking system showed a high inter- and intra-rater reliability and detected a tilted surface with respect to the floor plane. Every acquisition was characterised by an initial random offset. We estimated an average accuracy of 0.5 +/- 0.2 cm across the entire grid (XY-plane), noticing that the central points were more accurate (0.4 +/- 0.1 cm) than the outer ones (0.6 +/- 0.1 cm). For the Z-axis, the measurements showed greater variability and the accuracy was equal to 1.7 +/- 1.2 cm. Occlusion response was tested using nonparametric Bland-Altman statistics, which highlighted the robustness of the tracking system. In conclusion, our results promote the SteamVR system for static measures in the clinical field. The computed error can be considered clinically irrelevant for exercises aimed at the rehabilitation of functional movements, whose several motor outcomes are generally measured on the scale of metres

Sentry: development of an IMU-based holter for the ecological rehabilitation of the upper limb.

Movement analysis has become increasingly crucial in rehabilitation as a critical reference to plan therapeutic intervention in recent years. Despite being highly accurate, most of the available solutions on the market are limited to the clinical environment due to their cost and portability. During the rehabilitation period, the physiotherapist cannot follow the patient in the various delicate phases of the day. In periods of forced social distancing like the one we have recently experienced, the already limited medical visits may be further reduced, with the risk of decreasing treatment effectiveness. A possible solution may come from modern technologies, but at the moment, the available motion analysis devices are not affordable for private professionals to allow for ecological measurements, i.e. to collect data directly from the daily living scenario of the patient. Sentry is a wearable, non-invasive device that aims to answer most of these problems and is based on Inertial Measurement Units (IMUs). With an optimal trade-off between costs and portability, recent evidence promotes the use of IMUs in ecological measures to improve the effectiveness of the treatment. IMUs allow studying joints with more degrees of freedom at once for prolonged periods and without hindering the person's natural movement. This thesis presents the development and the performance estimation of an IMU-based device, with the development of both hardware and software to obtain a working prototype. The Sentry device includes two IMU sensors that can estimate the absolute orientation between the arm and the shoulder. Multiple tests have been performed using a robotic arm that executed repeated movements to evaluate repeatability, accuracy, and drift. These parameters were assessed under different speed values, positions and accelerations, reproducing the everyday conditions that a wearable device must withstand on a patient in the clinical phase. The sensors were also tested on a person in an actual use scenario to evaluate the effects of magnetic disturbance due to the environment, i.e. fields generated by electronic devices. Tests were carried out to evaluate the feasibility of this solution for ecological use, analysing aspects such as ease of use and repeatability of positioning (essential for use without the vigilance of the clinician) and battery life. The device was compared with the optoelectronic motion analysis system to analyse the planar shoulder movements of healthy people. The measurement uncertainties seem more than acceptable for the clinical applications targeted by the study, i.e., post-surgical limb rehabilitation. The limitations of the sensors are mainly related to magnetic disturbances such as hard and soft iron effects, which incidence can vary by application. It has been observed that this solution can respond to the needs of a rehabilitation environment that has to deal with an increasingly older population in developed countries and therefore requires all possible solutions to make the rehabilitation process more efficient