Affective Stimuli for an Auditory P300 Brain-Computer Interface

Gaze-independent brain computer interfaces (BCIs) are a potential communication tool for persons with paralysis. This study applies affective auditory stimuli to investigate their effects using a P300 BCI. Fifteen able-bodied participants operated the P300 BCI, with positive and negative affective sounds (PA: a meowing cat sound, NA: a screaming cat sound). Permuted stimuli of the positive and negative affective sounds (permuted-PA, permuted-NA) were also used for comparison. Electroencephalography data was collected, and offline classification accuracies were compared. We used a visual analog scale (VAS) to measure positive and negative affective feelings in the participants. The mean classification accuracies were 84.7% for PA and 67.3% for permuted-PA, while the VAS scores were 58.5 for PA and −12.1 for permuted-PA. The positive affective stimulus showed significantly higher accuracy and VAS scores than the negative affective stimulus. In contrast, mean classification accuracies were 77.3% for NA and 76.0% for permuted-NA, while the VAS scores were −50.0 for NA and −39.2 for permuted NA, which are not significantly different. We determined that a positive affective stimulus with accompanying positive affective feelings significantly improved BCI accuracy. Additionally, an ALS patient achieved 90% online classification accuracy. These results suggest that affective stimuli may be useful for preparing a practical auditory BCI system for patients with disabilities

Lower In-Hospital Mortality With Beta-Blocker Use at Admission in Patients With Acute Decompensated Heart Failure

[Background] It remains unclear whether beta‐blocker use at hospital admission is associated with better in‐hospital outcomes in patients with acute decompensated heart failure. [Methods and Results] We evaluated the factors independently associated with beta‐blocker use at admission, and the effect of beta‐blocker use at admission on in‐hospital mortality in 3817 patients with acute decompensated heart failure enrolled in the Kyoto Congestive Heart Failure registry. There were 1512 patients (39.7%) receiving, and 2305 patients (60.3%) not receiving beta‐blockers at admission for the index acute decompensated heart failure hospitalization. Factors independently associated with beta‐blocker use at admission were previous heart failure hospitalization, history of myocardial infarction, atrial fibrillation, cardiomyopathy, and estimated glomerular filtration rate <30 mL/min per 1.73 m2. Factors independently associated with no beta‐blocker use were asthma, chronic obstructive pulmonary disease, lower body mass index, dementia, older age, and left ventricular ejection fraction <40%. Patients on beta‐blockers had significantly lower in‐hospital mortality rates (4.4% versus 7.6%, P<0.001). Even after adjusting for confounders, beta‐blocker use at admission remained significantly associated with lower in‐hospital mortality risk (odds ratio, 0.41; 95% CI, 0.27–0.60, P<0.001). Furthermore, beta‐blocker use at admission was significantly associated with both lower cardiovascular mortality risk and lower noncardiovascular mortality risk. The association of beta‐blocker use with lower in‐hospital mortality risk was relatively more prominent in patients receiving high dose beta‐blockers. The magnitude of the effect of beta‐blocker use was greater in patients with previous heart failure hospitalization than in patients without (P for interaction 0.04). [Conclusions] Beta‐blocker use at admission was associated with lower in‐hospital mortality in patients with acute decompensated heart failure

Data from: Body ownership and agency altered by an electromyographically-controlled robotic arm

Understanding how we consciously experience our bodies is a fundamental issue in cognitive neuroscience. Two fundamental components of this are the sense of body ownership (the experience of the body as one’s own) and the sense of agency (the feeling of control over one’s bodily actions). These constructs have been used to investigate the incorporation of prostheses. To date, however, no evidence has been provided showing whether representations of ownership and agency in amputees are altered when operating a robotic prosthesis. Here we investigated a robotic arm using myoelectric control, for which the user varied the joint position continuously, in a rubber hand illusion task. Fifteen able-bodied participants and three trans-radial amputees were instructed to contract their wrist flexors/extensors alternately, and to watch the robotic arm move. The sense of ownership in both groups was extended to the robotic arm when the wrists of the real and robotic arm were flexed/extended synchronously, with the effect being smaller when they moved in opposite directions. Both groups also experienced a sense of agency over the robotic arm. These results suggest that these experimental settings induced successful incorporation of the prosthesis, at least for the amputees who took part in the present study

Confidence-aware self-supervised learning for dense monocular depth estimation in dynamic laparoscopic scene

Abstract This paper tackles the challenge of accurate depth estimation from monocular laparoscopic images in dynamic surgical environments. The lack of reliable ground truth due to inconsistencies within these images makes this a complex task. Further complicating the learning process is the presence of noise elements like bleeding and smoke. We propose a model learning framework that uses a generic laparoscopic surgery video dataset for training, aimed at achieving precise monocular depth estimation in dynamic surgical settings. The architecture employs binocular disparity confidence information as a self-supervisory signal, along with the disparity information from a stereo laparoscope. Our method ensures robust learning amidst outliers, influenced by tissue deformation, smoke, and surgical instruments, by utilizing a unique loss function. This function adjusts the selection and weighting of depth data for learning based on their given confidence. We trained the model using the Hamlyn Dataset and verified it with Hamlyn Dataset test data and a static dataset. The results show exceptional generalization performance and efficacy for various scene dynamics, laparoscope types, and surgical sites