RESUMO
Background: Stroke is a widespread and complex health issue, with many survivors requiring long-term rehabilitation due to upper-limb impairment. This study is aimed at comparing the perceived usability of two feedback-based stroke therapies: conventional mirror therapy (MT) and immersive virtual reality mirror therapy (VR). Methods: The study involved 45 participants, divided into three groups: the stroke survivors (n = 15), stroke-free older adults (n = 15), and young controls (n = 15). Participants performed two tasks using both MT and VR in a semirandom sequence. Usability instruments (SUS and NASA-TLX) were applied at the end of the activities, along with two experience-related questions. Results: The results indicated that both MT and VR had similar levels of perceived usability, with MT being more adaptable and causing less overall discomfort. Conversely, VR increased the perception of task difficulty and prevented participants from diverting their attention from the mirror-based feedback. Conclusion: While VR was found to be less comfortable than MT, both systems exhibited similar perceived usability. The comfort levels of the goggles may play a crucial role in determining the usability of VR for upper limb rehabilitation after stroke.
RESUMO
In this paper, a semi-automatic multi-object tracking method to track a group of unmarked zebrafish is proposed. This method can handle partial occlusion cases, maintaining the correct identity of each individual. For every object, we extracted a set of geometric features to be used in the two main stages of the algorithm. The first stage selected the best candidate, based both on the blobs identified in the image and the estimate generated by a Kalman Filter instance. In the second stage, if the same candidate-blob is selected by two or more instances, a blob-partitioning algorithm takes place in order to split this blob and reestablish the instances' identities. If the algorithm cannot determine the identity of a blob, a manual intervention is required. This procedure was compared against a manual labeled ground truth on four video sequences with different numbers of fish and spatial resolution. The performance of the proposed method is then compared against two well-known zebrafish tracking methods found in the literature: one that treats occlusion scenarios and one that only track fish that are not in occlusion. Based on the data set used, the proposed method outperforms the first method in correctly separating fish in occlusion, increasing its efficiency by at least 8.15% of the cases. As for the second, the proposed method's overall performance outperformed the second in some of the tested videos, especially those with lower image quality, because the second method requires high-spatial resolution images, which is not a requirement for the proposed method. Yet, the proposed method was able to separate fish involved in occlusion and correctly assign its identity in up to 87.85% of the cases, without accounting for user intervention.
