Ex-vivo systems for neuromodulation: A comparison of ex-vivo and in-vivo large animal nerve electrophysiology.

BACKGROUND: Little research exists on extending ex-vivo systems to large animal nerves, and to the best of our knowledge, there has yet to be a study comparing these against in-vivo data. This paper details the first ex-vivo system for large animal peripheral nerves to be compared with in-vivo results. NEW METHOD: Detailed ex-vivo and in-vivo closed-loop neuromodulation experiments were conducted on pig ulnar nerves. Temperatures from 20 °C to 37 °C were evaluated for the ex-vivo system. The data were analysed in the time and velocity domains, and a regression analysis established how evoked compound action potential amplitude and modal conduction velocity (CV) varied with temperature and time after explantation. MAIN RESULTS: Pig ulnar nerves were sustained ex-vivo up to 5 h post-explantation. CV distributions of ex-vivo and in-vivo data were compared, showing closer correspondence at 37 °C. Regression analysis results also demonstrated that modal CV and time since explantation were negatively correlated, whereas modal CV and temperature were positively correlated. COMPARISON WITH EXISTING METHODS: Previous ex-vivo systems were primarily aimed at small animal nerves, and we are not aware of an ex-vivo system to be directly compared with in-vivo data. This new approach provides a route to understand how ex-vivo systems for large animal nerves can be developed and compared with in-vivo data. CONCLUSION: The proposed ex-vivo system results were compared with those seen in-vivo, providing new insights into large animal nerve activity post-explantation. Such a system is crucial for complementing in-vivo experiments, maximising collected experimental data, and accelerating neural interface development.

Denoising and decoding spontaneous vagus nerve recordings with machine learning.

Neural interfaces that electrically stimulate the peripheral nervous system have been shown to successfully improve symptom management for several conditions, such as epilepsy and depression. A crucial part for closing the loop and improving the efficacy of implantable neuromodulation devices is the efficient extraction of meaningful information from nerve recordings, which can have a low Signal-to-Noise ratio (SNR) and non-stationary noise. In recent years, machine learning (ML) models have shown outstanding performance in regression and classification problems, but it is often unclear how to translate and assess these for novel tasks in biomedical engineering. This paper aims to adapt existing ML algorithms to carry out unsupervised denoising of neural recordings instead. This is achieved by applying bandpass filtering and two novel ML algorithms to in-vivo spontaneous, low-SNR vagus nerve recordings. The performance of each approach is compared using the task of extracting respiratory afferent activity and validated using cross-correlation, MSE, and accuracy in terms of extracting the true respiratory rate. A variational autoencoder (VAE) model in particular produces results that show better correlation with respiratory activity compared to bandpass filtering, highlighting that these models have the potential to preserve relevant features in complex neural recordings.

Does It par-Tickle?: Investigating the Relationship Between Mid-Air Haptics and Visual Representations of Surface Textures.

Mid-air haptic feedback technology produces tactile sensations that are felt without the need for physical interactions. However, mid-air haptic experiences need to be congruent with visual cues to reflect user expectations. To overcome this, we investigate how to visually present properties of objects, so that what one feels is a more accurate prediction of what one sees. Specifically, this paper investigates the relationship between 8 visual parameters of a point-cloud representation of a surface (particle color, size, distribution, etc.) and 4 mid-air haptic spatial modulation frequencies (20, 40, 60 and 80 Hz). Our results and analysis reveal a statistical significance between low and high-frequency modulations and particle density, particle bumpiness (depth) and particle arrangement (randomness).

Virtual-reality exergaming improves performance during high-intensity interval training.

Purpose: To determine if: (i) mean power output and enjoyment of high-intensity interval training (HIIT) are enhanced by virtual-reality (VR)-exergaming (track mode) compared to standard ergometry (blank mode), (ii) if mean power output of HIIT can be increased by allowing participants to race against their own performance (ghost mode) or by increasing the resistance (hard mode), without compromising exercise enjoyment. Methods: Sixteen participants (8 males, 8 females, VO2max: 41.2 ± 10.8 ml-1·kg-1·min-1) completed four VR-HIIT conditions in a partially-randomised cross-over study; (1a) blank, (1b) track, (2a) ghost, and (2b) hard. VR-HIIT sessions consisted of eight 60 s high-intensity intervals at a resistance equivalent to 70% (77% for hard) maximum power output (PMAX), interspersed by 60 s recovery intervals at 12.5% PMAX, at a self-selected cadence. Expired gases were collected and VO2 measured continuously. Post-exercise questionnaires were administered to identify differences in indices related to intrinsic motivation, subjective vitality, and future exercise intentions. Results: Enjoyment was higher for track vs. blank (difference: 0.9; 95% CI: 0.6, 1.3) with no other differences between conditions. There was no difference in mean power output for track vs. blank, however it was higher for track vs. ghost (difference: 5 Watts; CI: 3, 7), and hard vs. ghost (difference: 19 Watts; 95% CI: 15, 23). Conclusions: These findings demonstrate that VR-exergaming is an effective intervention to increase enjoyment during a single bout of HIIT in untrained individuals. The presence of a ghost may be an effective method to increase exercise intensity of VR-HIIT.

Reviewing the Evidence: In Pursuit of a Framework for Parkinson Disease Rehabilitation with Games.

Exercise gaming has been receiving a significant interest from both consumers and researchers. Be it for the purposes of weight loss, physical fitness or even just enjoyment, the potential of games to support rehabilitation has also been under investigation for a while. Due to our aging society, game based therapies could be a solution for optimizing resources and reducing rehabilitation costs. This paper aims to discuss the potential capacity of games as systems to enhance the relation of physical exercise and cognition for the rehabilitation of Parkinson Disease. Our investigation demonstrates that there is no established methodology for games in rehabilitation of Parkinson's addressing how games can encapsulate physical exercise strategies while providing safety, continuous monitoring and cognitive development exercises in facilitation of rehabilitation. Since rehabilitation with games is trending, yet to be developed rehabilitation strategies would benefit from new insights into the relationship between game worlds, physical exercise and motor-cognitive training. Therefore, it is useful to do further research into realizing (1) a relational model that demonstrates the relation between game world (composed of game features including formal game elements, audio-visual features, mechanics and dynamics), motor skills, cognition and physical exercise for both generic and specific rehabilitation purposes, (2) a structured task creation approach for game features that reconciles specific rehabilitation outcomes, correct level of engagement, task difficulty and safety requirements for target demographic.

Designing and evaluating a patient-centred health management system for seniors.

INTRODUCTION: Telehealth has been widely promoted as a technology to make healthcare more effective and affordable. However, current telehealth systems suffer from vendor lock-in and high cost, and are designed for managing chronic diseases rather than preventing them. METHODS: We address shortcomings of existing consumer-level health informatics applications in supporting senior health consumers, and provide designers of such systems with a design framework. We assess the feasibility of patient-centred health management systems (HMSs) that are designed based on the proposed framework. In contrast to traditional telehealth, HMSs are patient centred and aim at enabling health consumers to take control of their own health by providing functionality for health self-management. Quantitative and qualitative methods were adopted in evaluating a prototype HMS. RESULTS: Senior healthcare consumers viewed our HMS prototype positively, and experienced a positive change in their attitude towards their health. We identified requirements and challenges for HMSs. In particular, participants indicated that social networking features must have a clear purpose beyond simple broadcasting of emotions and opinions. DISCUSSION: Our study indicates that seniors are able and motivated to leverage a web-based patient-centred HMS, provided that there are suitable health support applications tailored to their needs. This could be achieved by making it attractive for third party application developers to contribute HMS content.