Investigating Activity Recognition for Hemiparetic Stroke Patients Using Wearable Sensors: A Deep Learning Approach with Data Augmentation.

Measuring the daily use of an affected limb after hospital discharge is crucial for hemiparetic stroke rehabilitation. Classifying movements using non-intrusive wearable sensors provides context for arm use and is essential for the development of a home rehabilitation system. However, the movement classification of stroke patients poses unique challenges, including variability and sparsity. To address these challenges, we collected movement data from 15 hemiparetic stroke patients (Stroke group) and 29 non-disabled individuals (ND group). The participants performed two different tasks, the range of motion (14 movements) task and the activities of daily living (56 movements) task, wearing five inertial measurement units in a home setting. We trained a 1D convolutional neural network and evaluated its performance for different training groups: ND-only, Stroke-only, and ND and Stroke jointly. We further compared the model performance with data augmentation from axis rotation and investigated how the performance varied based on the asymmetry of movements. The joint training of ND + Stroke yielded an increased F1-score by a margin of 31.6% and 10.6% compared to ND-only training and Stroke-only training, respectively. Data augmentation further enhanced F1-scores across all conditions by an average of 11.3%. Finally, asymmetric movements decreased the F1-score by 25.9% compared to symmetric movements in the Stroke group, indicating the importance of asymmetry in movement classification.

The relationship between person-centred care and the intensive care unit experience of critically ill patients: A multicentre cross-sectional survey.

BACKGROUND: Person-centred care has the potential to improve the patient experience in the intensive care unit (ICU). However, the relationship between person-centred care perceived by critically ill patients and their ICU experience has yet to be determined. OBJECTIVES: The aim of this study was to investigate the relationship between person-centred care and the ICU experience of critically ill patients. METHODS: This study was a multicentre, cross-sectional survey involving 19 ICUs of four university hospitals in Busan, Korea. The survey was conducted from June 2019 to July 2020, and 787 patients who had been admitted to the ICU for more than 24 hours participated. We measured person-centred care using the Person-Centered Critical Care Nursing perceived by Patient Questionnaire. Participants' ICU experience was measured by the Korean version of the Intensive Care Experience Questionnaire that consists of four subscales. We analysed the relationship between person-centred care and each area of the ICU experience using multivariate linear regression. RESULTS: Person-centred care was associated with 'awareness of surroundings' (ß = 0.29, p < .001), 'frightening experiences' (ß = -0.31, p < .001), and 'satisfaction with care' (ß = 0.54, p < .001). However, there was no significant association between person-centred care and 'recall of experience'. CONCLUSIONS: We observed that person-centred care was positively related to most of the ICU experiences of critically ill patients except for recall of experience. Further studies on developing person-centred nursing interventions are needed.