Objective structured clinical examination to teach competency in planetary health care and management - a prospective observational study.

Background: Health professionals are increasingly called upon and willing to engage in planetary health care and management. However, so far, this topic is rarely covered in medical curricula. As the need for professional communication is particularly high in this subject area, this study aimed to evaluate whether the objective structured clinical examination (OSCE) could be used as an accompanying teaching tool.

Wireless transmission of neural signals using entropy and mutual information compression.

Two of the most critical tasks when designing a portable wireless neural recording system are to limit power consumption and to efficiently use the limited bandwidth. It is known that for most wireless devices the majority of power is consumed by the wireless transmitter and it often represents the bottleneck of the overall design. This paper compares two compression techniques that take advantage of the sparseness of the neural spikes in neural recordings using an information theoretic formalism to enhance the well-established vector quantization (VQ) algorithm.

Wireless transmission of neuronal recordings using a portable real-time discrimination/compression algorithm.

A design challenge of portable wireless neural recording systems is the tradeoff between bandwidth and power consumption. This paper investigates the compression of neuronal recordings in real-time using a novel discriminating Linde-Buzo-Gray algorithm (DLBG) that preserves spike shapes while filtering background noise. The technique is implemented in a low power digital signal processor (DSP) which is capable of wirelessly transmitting raw neuronal recordings.

A reconfigurable neural signal processor (NSP) for brain machine interfaces.

In this paper, we present a design for a wearable computational DSP system that alleviates the issues of a previous design and provides a much smaller and lower power solution for the overall BMI goals. The system first acquires the neural data through a high speed data bus in order to train and evaluate prediction models. Then it wirelessly transmits the predicted results to a simulated robot arm.