Multimodal Approach to Assess a Virtual Reality-based Surgical Training Platform.

Virtual reality (VR) can bring numerous benefits to the learning process. Combining a VR environment with physiological sensors can be beneficial in skill assessment. We aim to investigate trainees' physiological (ECG) and behavioral differences during the virtual reality-based surgical training environment. Our finding showed a significant association between the VR-Score and all participants' total NASA-TLX workload score. The extent of the NASA-TLX workload score was negatively correlated with VR-Score (R2 =0.15, P < 0.03). In time-domain ECG analysis, we found that RMSSD (R2 =0.16, P < 0.05) and pNN50 (R2 =0.15, P < 0.05) scores correlated with significantly higher VR-score of all participants. In this study, we used SVM (linear kernel) and Logistic Regression classification techniques to classify the participants as gamers and non-gamers using data from VR headsets. Both SVM and Logistic Regression accurately classified the participants as gamers and non-gamers with 83% accuracy. For both SVM and Linear Regression, precision was noted as 88%, recall as 83%, and f1-score as 83%. There is increasing interest in characterizing trainees' physiological and behavioral activity profiles in a VR environment, aiming to develop better training and assessment methodologies.

Video game experience affects performance, cognitive load, and brain activity in laparoscopic surgery training.

Objectives: Video games can be a valuable tool for surgery training. Individuals who interact or play video games tend to have a better visuospatial ability when compared to non-gamers. Numerous studies suggest that video game experience is associated with faster acquisition, greater sharpening, and longer retention of laparoscopic skills. Given the neurocognitive complexity of surgery skill, multimodal approaches are required to understand how video game playing enhances laparoscopy skill. Material and Methods: Twenty-seven students with no laparoscopy experience and varying levels of video game experience performed standard laparoscopic training tasks. Their performance, subjective cognitive loading, and prefrontal cortical activity were recorded and analyzed. As a reference point to use in comparing the two novice groups, we also included data from 13 surgeons with varying levels of laparoscopy experience and no video game experience. Results: Results indicated that video game experience was correlated with higher performance (R2 = 0.22, p <0.01) and lower cognitive load (R2 = 0.21, p <0.001), and the prefrontal cortical activation of students with gaming experience was relatively lower than those without gaming experience. In terms of these variables, gaming experience in novices tended to produce effects similar to those of laparoscopy experience in surgeons. Conclusion: Our results suggest that along the dimensions of performance, cognitive load, and brain activity, the effects of video gaming experience on novice laparoscopy trainees are similar to those of real-world laparoscopy experience on surgeons. We believe that the neural underpinnings of surgery skill and its links with gaming experience need to be investigated further using wearable functional brain imaging.

Screening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopy.

Introduction: Alzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment. Currently, 50 million people live with dementia worldwide, and there are nearly 10 million new cases every year. There is a need for relatively less costly and more objective methods of screening and early diagnosis. Methods: Functional near-infrared spectroscopy (fNIRS) systems are a promising solution for the early Detection of AD. For a practical clinically relevant system, a smaller number of optimally placed channels are clearly preferable. In this study, we investigated the number and locations of the best-performing fNIRS channels measuring prefrontal cortex activations. Twenty-one subjects diagnosed with AD and eighteen healthy controls were recruited for the study. Results: We have shown that resting-state fNIRS recordings from a small number of prefrontal locations provide a promising methodology for detecting AD and monitoring its progression. A high-density continuous-wave fNIRS system was first used to verify the relatively lower hemodynamic activity in the prefrontal cortical areas observed in patients with AD. By using the episode averaged standard deviation of the oxyhemoglobin concentration changes as features that were fed into a Support Vector Machine; we then showed that the accuracy of subsets of optical channels in predicting the presence and severity of AD was significantly above chance. The results suggest that AD can be detected with a 0.76 sensitivity score and a 0.68 specificity score while the severity of AD could be detected with a 0.75 sensitivity score and a 0.72 specificity score with ≤5 channels. Discussion: These scores suggest that fNIRS is a viable technology for conveniently detecting and monitoring AD as well as investigating underlying mechanisms of disease progression.

High density optical neuroimaging predicts surgeons's subjective experience and skill levels.

Measuring cognitive load is important for surgical education and patient safety. Traditional approaches of measuring cognitive load of surgeons utilise behavioural metrics to measure performance and surveys and questionnaires to collect reports of subjective experience. These have disadvantages such as sporadic data, occasionally intrusive methodologies, subjective or misleading self-reporting. In addition, traditional approaches use subjective metrics that cannot distinguish between skill levels. Functional neuroimaging data was collected using a high density, wireless NIRS device from sixteen surgeons (11 attending surgeons and 5 surgery resident) and 17 students while they performed two laparoscopic tasks (Peg transfer and String pass). Participant's subjective mental load was assessed using the NASA-TLX survey. Machine learning approaches were used for predicting the subjective experience and skill levels. The Prefrontal cortex (PFC) activations were greater in students who reported higher-than-median task load, as measured by the NASA-TLX survey. However in the case of attending surgeons the opposite tendency was observed, namely higher activations in the lower v higher task loaded subjects. We found that response was greater in the left PFC of students particularly near the dorso- and ventrolateral areas. We quantified the ability of PFC activation to predict the differences in skill and task load using machine learning while focussing on the effects of NIRS channel separation distance on the results. Our results showed that the classification of skill level and subjective task load could be predicted based on PFC activation with an accuracy of nearly 90%. Our finding shows that there is sufficient information available in the optical signals to make accurate predictions about the surgeons' subjective experiences and skill levels. The high accuracy of results is encouraging and suggest the integration of the strategy developed in this study as a promising approach to design automated, more accurate and objective evaluation methods.

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance.

OBJECTIVE: Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system's ability to decode mental states and compare it with its unimodal components. APPROACH: We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. MAIN RESULTS: EEG+fNIRS's decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. SIGNIFICANCE: Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

Hemodynamic correlates of spontaneous neural activity measured by human whole-head resting state EEG+fNIRS.

The brains of awake, resting human subjects display spontaneously occurring neural activity patterns whose magnitude is typically many times greater than those triggered by cognitive or perceptual performance. Evoked and resting state activations affect local cerebral hemodynamic properties through processes collectively referred to as neurovascular coupling. Its investigation calls for an ability to track both the neural and vascular aspects of brain function. We used scalp electroencephalography (EEG), which provided a measure of the electrical potentials generated by cortical postsynaptic currents. Simultaneously we utilized functional near-infrared spectroscopy (NIRS) to continuously monitor hemoglobin concentration changes in superficial cortical layers. The multi-modal signal from 18 healthy adult subjects allowed us to investigate the association of neural activity in a range of frequencies over the whole-head to local changes in hemoglobin concentrations. Our results verified the delayed alpha (8-16Hz) modulation of hemodynamics in posterior areas known from the literature. They also indicated strong beta (16-32Hz) modulation of hemodynamics. Analysis revealed, however, that beta modulation was likely generated by the alpha-beta coupling in EEG. Signals from the inferior electrode sites were dominated by scalp muscle related activity. Our study aimed to characterize the phenomena related to neurovascular coupling observable by practical, cost-effective, and non-invasive multi-modal techniques.

Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.

Non-invasive Brain-Computer Interfaces (BCI) have demonstrated great promise for neuroprosthetics and assistive devices. Here we aim to investigate methods to combine Electroencephalography (EEG) and functional Near-Infrared Spectroscopy (fNIRS) in an asynchronous Sensory Motor rhythm (SMR)-based BCI. We attempted to classify 4 different executed movements, namely, Right-Arm-Left-Arm-Right-Hand-Left-Hand tasks. Previous studies demonstrated the benefit of EEG-fNIRS combination. However, since normally fNIRS hemodynamic response shows a long delay, we investigated new features, involving slope indicators, in order to immediately detect changes in the signals. Moreover, Common Spatial Patterns (CSPs) have been applied to both EEG and fNIRS signals. 15 healthy subjects took part in the experiments and since 25 trials per class were available, CSPs have been regularized with information from the entire population of participants and optimized using genetic algorithms. The different features have been compared in terms of performance and the dynamic accuracy over trials shows that the introduced methods diminish the fNIRS delay in the detection of changes.

Nanoliter droplet vitrification for oocyte cryopreservation.

AIM: Oocyte cryopreservation remains largely experimental, with live birth rates of only 2-4% per thawed oocyte. In this study, we present a nanoliter droplet technology for oocyte vitrification. MATERIALS & METHODS: An ejector-based droplet vitrification system was designed to continuously cryopreserve oocytes in nanoliter droplets. Oocyte survival rates, morphologies and parthenogenetic development after each vitrification step were assessed in comparison with fresh oocytes. RESULTS: Oocytes were retrieved after cryoprotectant agent loading/unloading, and nanoliter droplet encapsulation showed comparable survival rates to fresh oocytes after 24 h in culture. Also, oocytes recovered after vitrification/thawing showed similar morphologies to those of fresh oocytes. Additionally, the rate of oocyte parthenogenetic activation after nanoliter droplet encapsulation was comparable with that observed for fresh oocytes. This nanoliter droplet technology enables the vitrification of oocytes at higher cooling and warming rates using lower cryoprotectant agent levels (i.e., 1.4 M ethylene glycol, 1.1 M dimethyl sulfoxide and 1 M sucrose), thus making it a potential technology to improve oocyte cryopreservation outcomes.

Controlled viable release of selectively captured label-free cells in microchannels.

Selective capture of cells from bodily fluids in microchannels has broadly transformed medicine enabling circulating tumor cell isolation, rapid CD4(+) cell counting for HIV monitoring, and diagnosis of infectious diseases. Although cell capture methods have been demonstrated in microfluidic systems, the release of captured cells remains a significant challenge. Viable retrieval of captured label-free cells in microchannels will enable a new era in biological sciences by allowing cultivation and post-processing. The significant challenge in release comes from the fact that the cells adhere strongly to the microchannel surface, especially when immuno-based immobilization methods are used. Even though fluid shear and enzymes have been used to detach captured cells in microchannels, these methods are known to harm cells and affect cellular characteristics. This paper describes a new technology to release the selectively captured label-free cells in microchannels without the use of fluid shear or enzymes. We have successfully released the captured CD4(+) cells (3.6% of the mononuclear blood cells) from blood in microfluidic channels with high specificity (89% ± 8%), viability (94% ± 4%), and release efficiency (59% ± 4%). We have further validated our system by specifically capturing and controllably releasing the CD34(+) stem cells from whole blood, which were quantified to be 19 cells per million blood cells in the blood samples used in this study. Our results also indicated that both CD4(+) and CD34(+) cells released from the microchannels were healthy and amenable for in vitro culture. Manual flow based microfluidic method utilizes inexpensive, easy to fabricate microchannels allowing selective label-free cell capture and release in less than 10 minutes, which can also be used at the point-of-care. The presented technology can be used to isolate and purify a broad spectrum of cells from mixed populations offering widespread applications in applied biological sciences, such as tissue engineering, regenerative medicine, rare cell and stem cell isolation, proteomic/genomic research, and clonal/population analyses.

Lensless imaging for simultaneous microfluidic sperm monitoring and sorting.

5.3 million American couples of reproductive age (9%) are affected by infertility, among which male factors account for up to 50% of cases, which necessitates the identification of parameters defining sperm quality, including sperm count and motility. In vitro fertilization (IVF) with or without intra cytoplasmic sperm injection (ICSI) has become the most widely used assisted reproductive technology (ART) in modern clinical practice to overcome male infertility challenges. One of the obstacles of IVF and ICSI lies in identifying and isolating the most motile and presumably healthiest sperm from semen samples that have low sperm counts (oligozoospermia) and/or low sperm motility (oligospermaesthenia). Microfluidic systems have shown potential to sort sperm with flow systems. However, the small field of view (FOV) of conventional microscopes commonly used to image sperm motion presents challenges in tracking a large number of sperm cells simultaneously. To address this challenge, we have integrated a lensless charge-coupled device (CCD) with a microfluidic chip to enable wide FOV and automatic recording as the sperm move inside a microfluidic channel. The integrated system enables the sorting and tracking of a population of sperm that have been placed in a microfluidic channel. This channel can be monitored in both horizontal and vertical configuration similar to a swim-up column method used clinically. Sperm motilities can be quantified by tracing the shadow paths for individual sperm. Moreover, as the sperm are sorted by swimming from the inlet towards the outlet of a microfluidic channel, motile sperm that reach the outlet can be extracted from the channel at the end of the process. This technology can lead to methods to evaluate each sperm individually in terms of motility response in a wide field of view, which could prove especially useful, when working with oligozoospermic or oligospermaesthenic samples, in which the most motile sperm need to be isolated from a pool of small number of sperm.

Blood banking in living droplets.

Blood banking has a broad public health impact influencing millions of lives daily. It could potentially benefit from emerging biopreservation technologies. However, although vitrification has shown advantages over traditional cryopreservation techniques, it has not been incorporated into transfusion medicine mainly due to throughput challenges. Here, we present a scalable method that can vitrify red blood cells in microdroplets. This approach enables the vitrification of large volumes of blood in a short amount of time, and makes it a viable and scalable biotechnology tool for blood cryopreservation.

Layer by layer three-dimensional tissue epitaxy by cell-laden hydrogel droplets.

The ability to bioengineer three-dimensional (3D) tissues is a potentially powerful approach to treat diverse diseases such as cancer, loss of tissue function, or organ failure. Traditional tissue engineering methods, however, face challenges in fabricating 3D tissue constructs that resemble the native tissue microvasculature and microarchitectures. We have developed a bioprinter that can be used to print 3D patches of smooth muscle cells (5 mm x 5 mm x 81 microm) encapsulated within collagen. Current inkjet printing systems suffer from loss of cell viability and clogging. To overcome these limitations, we developed a system that uses mechanical valves to print high viscosity hydrogel precursors containing cells. The bioprinting platform that we developed enables (i) printing of multilayered 3D cell-laden hydrogel structures (16.2 microm thick per layer) with controlled spatial resolution (proximal axis: 18.0 +/- 7.0 microm and distal axis: 0.5 +/- 4.9 microm), (ii) high-throughput droplet generation (1 s per layer, 160 droplets/s), (iii) cell seeding uniformity (26 +/- 2 cells/mm(2) at 1 million cells/mL, 122 +/- 20 cells/mm(2) at 5 million cells/mL, and 216 +/- 38 cells/mm(2) at 10 million cells/mL), and (iv) long-term viability in culture (>90%, 14 days). This platform to print 3D tissue constructs may be beneficial for regenerative medicine applications by enabling the fabrication of printed replacement tissues.

Lensless imaging for point-of-care testing.

We show a platform that merges a microfluidic chip with lensless imaging for CD4(+) T-lymphocyte counting at resource-limited settings. To capture CD4(+) T lymphocytes, anti-CD4 antibody was immobilized on a microfluidic chip. The captured cells were detected by a charge coupled device (CCD) sensor using lensless shadow imaging techniques. Gray scale shadow images of captured cells on the chip (24 mm x 4 mm x 50 mum) were enumerated in three seconds using an automatic cell counting software. The device achieved 70.2 +/- 6.5% capture efficiency, 88.8 +/- 5.4% capture specificity for CD4(+) T-lymphocytes, 96 +/- 1.6% CCD efficiency, and 83.5 +/- 2.4% overall platform performance (n = 9 devices). This integrated platform has potential for point-of-care testing (POCT) to rapidly capture, image and count specific cell types from unprocessed whole blood.

Integrating microfluidics and lensless imaging for point-of-care testing.

We demonstrate an integrated platform that merges a microfluidic chip with lensless imaging to target CD4(+) T-lymphocyte counts for HIV point-of-care testing at resource-limited settings. The chips were designed and fabricated simply with a laser cutter without using expensive cleanroom equipment. To capture CD4(+) T-lymphocytes from blood, anti-CD4 antibody was immobilized on only one side of the microfluidic chip. These captured cells were detected through an optically clear chip using a charge coupled device (CCD) sensor by lensless shadow imaging techniques. Gray scale image of the captured cells in a 24 mm x 4 mm x 50 microm microfluidic chip was obtained by the lensless imaging platform. The automatic cell counting software enumerated the captured cells in 3s. Captured cells were also imaged with a fluorescence microscope and manually counted to characterize functionality of the integrated platform. The integrated platform achieved 70.2+/-6.5% capture efficiency, 88.8+/-5.4% capture specificity for CD4(+) T-lymphocytes, 96+/-1.6% CCD efficiency, and 83.5+/-2.4% overall platform performance (n=9 devices) compared to the gold standard, i.e. flow cytometry count. The integrated system gives a CD4 count from blood within 10 min. The integrated platform points a promising direction for point-of-care testing (POCT) to rapidly capture, image and count subpopulations of cells from blood samples in an automated matter.