State-of-the-Art Wearable Sensors and Possibilities for Radar in Fall Prevention.

Radar technology is constantly evolving, and new applications are arising, particularly for the millimeter wave bands. A novel application for radar is gait monitoring for fall prevention, which may play a key role in maintaining the quality of life of people as they age. Alarming statistics indicate that one in three adults aged 65 years or older will experience a fall every year. A review of the sensors used for gait analysis and their applications to technology-based fall prevention interventions was conducted, focusing on wearable devices and radar technology. Knowledge gaps were identified, such as wearable radar development, application specific signal processing and the use of machine learning algorithms for classification and risk assessment. Fall prevention through gait monitoring in the natural environment presents significant opportunities for further research. Wearable radar could be useful for measuring gait parameters and performing fall risk-assessment using statistical methods, and could also be used to monitor obstacles in real-time.

Neurobionics and the brain-computer interface: current applications and future horizons.

The brain-computer interface (BCI) is an exciting advance in neuroscience and engineering. In a motor BCI, electrical recordings from the motor cortex of paralysed humans are decoded by a computer and used to drive robotic arms or to restore movement in a paralysed hand by stimulating the muscles in the forearm. Simultaneously integrating a BCI with the sensory cortex will further enhance dexterity and fine control. BCIs are also being developed to: provide ambulation for paraplegic patients through controlling robotic exoskeletons; restore vision in people with acquired blindness; detect and control epileptic seizures; and improve control of movement disorders and memory enhancement. High-fidelity connectivity with small groups of neurons requires microelectrode placement in the cerebral cortex. Electrodes placed on the cortical surface are less invasive but produce inferior fidelity. Scalp surface recording using electroencephalography is much less precise. BCI technology is still in an early phase of development and awaits further technical improvements and larger multicentre clinical trials before wider clinical application and impact on the care of people with disabilities. There are also many ethical challenges to explore as this technology evolves.

A novel simulation paradigm utilising MRI-derived phosphene maps for cortical prosthetic vision.

Objective.We developed a realistic simulation paradigm for cortical prosthetic vision and investigated whether we can improve visual performance using a novel clustering algorithm.Approach.Cortical visual prostheses have been developed to restore sight by stimulating the visual cortex. To investigate the visual experience, previous studies have used uniform phosphene maps, which may not accurately capture generated phosphene map distributions of implant recipients. The current simulation paradigm was based on the Human Connectome Project retinotopy dataset and the placement of implants on the cortices from magnetic resonance imaging scans. Five unique retinotopic maps were derived using this method. To improve performance on these retinotopic maps, we enabled head scanning and a density-based clustering algorithm was then used to relocate centroids of visual stimuli. The impact of these improvements on visual detection performance was tested. Using spatially evenly distributed maps as a control, we recruited ten subjects and evaluated their performance across five sessions on the Berkeley Rudimentary Visual Acuity test and the object recognition task.Main results.Performance on control maps is significantly better than on retinotopic maps in both tasks. Both head scanning and the clustering algorithm showed the potential of improving visual ability across multiple sessions in the object recognition task.Significance.The current paradigm is the first that simulates the experience of cortical prosthetic vision based on brain scans and implant placement, which captures the spatial distribution of phosphenes more realistically. Utilisation of evenly distributed maps may overestimate the performance that visual prosthetics can restore. This simulation paradigm could be used in clinical practice when making plans for where best to implant cortical visual prostheses.

Utilization of brain scans to create realistic phosphene maps for cortical visual prosthesis simulation studies.

It has been shown that we can restore sensations of light by stimulating the visual cortex. Cortical prosthetic vision consists of light perception in the visual field named phosphenes. Phosphenes are like pixels on a monitor which we can control to form the desired perception. However, the locations of phosphenes evoked vary between individuals. One of the biggest challenges is how to utilize phosphenes to present recognizable patterns that represent real-world scenes. Because of the difficulties of recruiting participants, and the risks of neurosurgery, researchers have used computer simulations to investigate the outcome of cortical visual prostheses. Previous simulations used regular phosphene maps, which may overestimate the visual ability cortical visual prosthesis can provide. This study aims to develop a more realistic simulation for cortical visual prostheses. We derived realistic phosphene maps using an existing cortical retinotopy dataset and decided implant placement by considering neurosurgery restrictions. We rendered some visual stimuli to evaluate the usability of those phosphene maps. The results indicate that presenting information on phosphenes maps may be more challenging than previously estimated.

Electrical stimulation thresholds differ between V1 and V2.

Cortical visual prostheses are designed to treat blindness by restoring visual perceptions through artificial electrical stimulation of the primary visual cortex (V1). Intracortical microelectrodes produce the smallest visual percepts and thus higher resolution vision - like a higher density of pixels on a monitor. However, intracortical microelectrodes must maintain a minimum spacing to preserve tissue integrity. One solution to increase the density of percepts is to implant and stimulate multiple visual areas, such as V1 and V2, although the properties of microstimulation in V2 remain largely unexplored. We provide a direct comparison of V1 and V2 microstimulation in two common marmoset monkeys. We find similarities in response trends between V1 and V2 but differences in threshold, neural activity duration, and spread of activity at the threshold current. This has implications for using multi-area stimulation to increase the resolution of cortical visual prostheses.