The Utility of Smartphone-Based Thermal Imaging in the Management and Monitoring of Microvascular Flap Procedures: A Systematic Review and Meta-Analysis.

BACKGROUND: Smartphone-based thermal imaging (SBTI) has been reported in the literature to be an easy-to-use, contactless, cost-friendly alternative to standard imaging modalities in identifying flap perforators, monitoring flap perfusion, and detecting flap failure. Our systematic review and meta-analysis aimed to evaluate SBTI's accuracy in perforator identification and secondarily evaluate SBTI's utility in flap perfusion monitoring as well as ability to predict flap compromise, failure, and survival. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, a systematic review was performed using PubMed from inception to 2021. Articles were uploaded into Covidence and, following duplicate deletion, were initially screened for use of SBTI in flap procedures through title and abstract screening followed by full-text review. The following data points, if provided, were extracted from each included study: study design, number of patients, patient demographics, perforator number and location, flap number and location, room temperature, cooling method, imaging distance, time from cloth removal, primary (SBTI's accuracy in perforator identification), and secondary outcomes (prediction of flap compromise/failure/survival and cost analysis). Meta-analysis was performed using RevMan v.5. RESULTS: The initial search yielded 153 articles. Eleven applicable studies with a total of 430 flaps from 416 patients were ultimately included. The SBTI device assessed in all included studies was FLIR ONE. Four studies assessed the SBTI's perforated detection ability and were included in meta-analysis. Smartphone-based thermal imaging correctly identified 378 (93.3%; n = 405) perforators, and computed tomography angiography (CTA) correctly identified 402 (99.2%; n = 402), although in one study SBTI found additional perforators not detected on CTA. A random-effects model was used (I2 = 65%), and no significant difference in perforator detection ability was found between SBTI and CTA (P = 0.27). CONCLUSIONS: This systematic review and meta-analysis supports SBTI as user- and cost-friendly ($229.99), contactless imaging modality with perforator detection ability comparable to current criterion-standard CTA. Postoperatively, SBTI outperformed Doppler ultrasound in early detection of microvascular changes causing flap compromise, allowing for prompt tissue salvage. With a minimal learning curve, SBTI seems to be a promising method of postoperative flap perfusion monitoring able to be used by all hospital ranks. Smartphone-based thermal imaging could thus increase flap monitoring frequency and lower complication rates, although further study is warranted.

Same Day Discharge After Mastectomy and Immediate Implant-Based Breast Reconstruction: A Retrospective Cohort Comparison Using the National Surgical Quality Improvement Program Database.

INTRODUCTION: Currently, overnight admission after immediate implant-based breast reconstruction (IBR) is the standard of care. Our study aims to analyze the safety, feasibility, and outcomes of immediate IBR with same-day discharge as compared with the standard overnight stay. METHODS: The 2015-2020 National Surgical Quality Improvement Program database was reviewed to identify all patients undergoing mastectomy with immediate IBR for malignant breast disease. Patients were stratified into study (patients discharged day of surgery) and control (patients admitted after surgery) groups. Patient demographics, comorbidities, surgical characteristics, implant type, wound complications, readmission, and reoperation rates were collected and analyzed. Univariate and multivariate logistic regression was used to determine independent predictors of same-day discharge versus admission. In addition, Pearson χ2 test was used for comparison of proportions and t test was used for continuous variables unless distributions required subsequent nonparametric analyses. Statistical significance was defined as a P value less than 0.05. RESULTS: A total of 21,923 cases were identified. The study group included 1361 patients discharged same day and the control group included 20,562 patient s admitted for average of 1.4 days (range, 1-86). Average age was 51 years for both groups. Average body mass index for the study group 27 and 28 kg/m2 for the control group, respectively. Total wound complication rates were similar (4.5% study, 4.3% control, P = 0.72). Reoperation rates were lower with same-day discharge (5.7% study, 6.8% control, P = 0.105), though not statistically significant. However, same-day discharge patients had a significantly lower readmission rate compared with the control (2.3% study, 4.2% control, P = 0.001). CONCLUSION: National Surgical Quality Improvement Program data analysis over a 6-year period reveals that immediate IBR with same-day discharge is associated with a significantly lower readmission rate when compared with the standard overnight stay. The comparable complication profiles show that immediate IBR with same-day discharge is safe, potentially benefiting both patients and hospitals.

Risk factors associated with 30-day complications following lower extremity sarcoma surgery: A national surgical quality improvement project analysis.

BACKGROUND: Our study aims to identify risk factors associated with complications in lower extremity (LE) sarcoma surgery, as well as the prevalence and complications associated with concurrent plastic surgery procedures (CPSP). METHODS: ACS-NSQIP database was accessed to identify patients treated for LE sarcoma (2010-2019). Patient demographics, preoperative lab, comorbidities, tumor type, location, principle procedure, and presence/characteristics of CPSPs were recorded. Thirty-day soft tissue complications were analyzed. Bivariate and multivariate logistic regression was performed on IBM SPSS.™ RESULTS: Nine hundred eighteen patients were included (483 males and 435 females), average age and body mass index (BMI) of 57 and 27.4 kg/m,2 respectively. Comorbidities included smoking (13.9%, 128), hypertension (37.3%, 342), and insulin-dependent diabetes (3.7%, 34). Preoperative lab values included albumin <3.5 (6.8%, 63), hematocrit <30% (8.2%, 75), and platelet count <150 000 (5.9%, 54). Thirty-day soft tissue complication rate was 5.7% (52 of 918). On multivariate logistic regression, increased age (p = 0.039), higher BMI (p = 0.017), and longer operative times (p = 0.002) were significant risk factors independently associated with soft tissue complications. CONCLUSIONS: Soft tissue complications within 30 days occur in 6% of patients. Graft procedures carry a 20% risk of complications. Risk factors independently associated with complications include increased age, increased BMI, and longer operative times.

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low Vision.

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed sensor infrastructure, which is costly, time-consuming, and/or often infeasible at scale. Herein, we propose a novel vision-based localization pipeline for a specific use case: navigation support for end users with blindness and low vision. Given a query image taken by an end user on a mobile application, the pipeline leverages a visual place recognition (VPR) algorithm to find similar images in a reference image database of the target space. The geolocations of these similar images are utilized in a downstream task that employs a weighted-average method to estimate the end user's location. Another downstream task utilizes the perspective-n-point (PnP) algorithm to estimate the end user's direction by exploiting the 2D-3D point correspondences between the query image and the 3D environment, as extracted from matched images in the database. Additionally, this system implements Dijkstra's algorithm to calculate a shortest path based on a navigable map that includes the trip origin and destination. The topometric map used for localization and navigation is built using a customized graphical user interface that projects a 3D reconstructed sparse map, built from a sequence of images, to the corresponding a priori 2D floor plan. Sequential images used for map construction can be collected in a pre-mapping step or scavenged through public databases/citizen science. The end-to-end system can be installed on any internet-accessible device with a camera that hosts a custom mobile application. For evaluation purposes, mapping and localization were tested in a complex hospital environment. The evaluation results demonstrate that our system can achieve localization with an average error of less than 1 m without knowledge of the camera's intrinsic parameters, such as focal length.

Dysfunctional mode switching between fixation and saccades: collaborative insights into two unusual clinical disorders.

Voluntary rapid eye movements (saccades) redirect the fovea toward objects of visual interest. The saccadic system can be considered as a dual-mode system: in one mode the eye is fixating, in the other it is making a saccade. In this review, we consider two examples of dysfunctional saccades, interrupted saccades in late-onset Tay-Sachs disease and gaze-position dependent opsoclonus after concussion, which fail to properly shift between fixation and saccade modes. Insights and benefits gained from bi-directional collaborative exchange between clinical and basic scientists are emphasized. In the case of interrupted saccades, existing mathematical models were sufficiently detailed to provide support for the cause of interrupted saccades. In the case of gaze-position dependent opsoclonus, existing models could not explain the behavior, but further development provided a reasonable hypothesis for the mechanism underlying the behavior. Collaboration between clinical and basic science is a rich source of progress for developing biologically plausible models and understanding neurological disease. Approaching a clinical problem with a specific hypothesis (model) in mind often prompts new experimental tests and provides insights into basic mechanisms.

How sandbag-able are concussion sideline assessments? A close look at eye movements to uncover strategies.

Background: Sideline diagnostic tests for concussion are vulnerable to volitional poor performance ("sandbagging") on baseline assessments, motivated by desire to subvert concussion detection and potential removal from play. We investigated eye movements during sandbagging versus best effort on the King-Devick (KD) test, a rapid automatized naming (RAN) task.Methods: Participants performed KD testing during oculography following instructions to sandbag or give best effort.Results: Twenty healthy participants without concussion history were included (mean age 27 ± 8 years). Sandbagging resulted in longer test times (89.6 ± 39.2 s vs 48.2 ± 8.5 s, p < .001), longer inter-saccadic intervals (459.5 ± 125.4 ms vs 311.2 ± 79.1 ms, p < .001) and greater numbers of saccades (171.4 ± 47 vs 138 ± 24.2, p < .001) and reverse saccades (wrong direction for reading) (21.2% vs 11.3%, p < .001). Sandbagging was detectable using a logistic model with KD times as the only predictor, though more robustly detectable using eye movement metrics.Conclusions: KD sandbagging results in eye movement differences that are detectable by eye movement recordings and suggest an invalid test score. Objective eye movement recording during the KD test shows promise for distinguishing between best effort and post-injury performance, as well as for identifying sandbagging red flags.

Detection of normal and slow saccades using implicit piecewise polynomial approximation.

The quantitative analysis of saccades in eye movement data unveils information associated with intention, cognition, and health status. Abnormally slow saccades are indicative of neurological disorders and often imply a specific pathological disturbance. However, conventional saccade detection algorithms are not designed to detect slow saccades, and are correspondingly unreliable when saccades are unusually slow. In this article, we propose an algorithm that is effective for the detection of both normal and slow saccades. The proposed algorithm is partly based on modeling saccadic waveforms as piecewise-quadratic signals. The algorithm first decreases noise in acquired eye-tracking data using optimization to minimize a prescribed objective function, then uses velocity thresholding to detect saccades. Using both simulated saccades and real saccades generated by healthy subjects and patients, we evaluate the performance of the proposed algorithm and 10 other detection algorithms. We show the proposed algorithm is more accurate in detecting both normal and slow saccades than other algorithms.

Did I do that? Detecting a perturbation to visual feedback in a reaching task.

The motor system executes actions in a highly stereotyped manner despite the high number of degrees of freedom available. Studies of motor adaptation leverage this fact by disrupting, or perturbing, visual feedback to measure how the motor system compensates. To elicit detectable effects, perturbations are often large compared to trial-to-trial reach endpoint variability. However, awareness of large perturbations can elicit qualitatively different compensation processes than unnoticeable ones can. The current experiment measures the perturbation detection threshold, and investigates how humans combine proprioception and vision to decide whether displayed reach endpoint errors are self-generated only, or are due to experimenter-imposed perturbation. We scaled or rotated the position of the visual feedback of center-out reaches to targets and asked subjects to indicate whether visual feedback was perturbed. Subjects detected perturbations when they were at least 1.5 times the standard deviation of trial-to-trial endpoint variability. In contrast to previous studies, subjects suboptimally combined vision and proprioception. Instead of using proprioceptive input, they responded based on the final (possibly perturbed) visual feedback. These results inform methodology in motor system experimentation, and more broadly highlight the ability to attribute errors to one's own motor output and combine visual and proprioceptive feedback to make decisions.

Rapid Number Naming and Quantitative Eye Movements May Reflect Contact Sport Exposure in a Collegiate Ice Hockey Cohort.

BACKGROUND: The King-Devick (K-D) test of rapid number naming is a reliable visual performance measure that is a sensitive sideline indicator of concussion when time scores worsen (lengthen) from preseason baseline. Within cohorts of youth athletes <18 years old, baseline K-D times become faster with increasing age. We determined the relation of rapid number-naming time scores on the K-D test to electronic measurements of saccade performance during preseason baseline assessments in a collegiate ice hockey team cohort. Within this group of young adult athletes, we also sought to examine the potential role for player age in determining baseline scores. METHODS: Athletes from a collegiate ice hockey team received preseason baseline testing as part of an ongoing study of rapid rink-side performance measures for concussion. These included the K-D test (spiral-bound cards and tablet computer versions). Participants also performed a laboratory-based version of the K-D test with simultaneous infrared-based video-oculographic recordings using an EyeLink 1000+. This allowed measurement of the temporal and spatial characteristics of eye movements, including saccadic velocity, duration, and intersaccadic interval (ISI). RESULTS: Among 13 male athletes, aged 18-23 years (mean 20.5 ± 1.6 years), prolongation of the ISI (a combined measure of saccade latency and fixation duration) was the measure most associated with slower baseline time scores for the EyeLink-paired K-D (mean 38.2 ± 6.2 seconds, r = 0.88 [95% CI 0.63-0.96], P = 0.0001), the K-D spiral-bound cards (36.6 ± 5.9 seconds, r = 0.60 [95% CI 0.08-0.87], P = 0.03), and K-D computerized tablet version (39.1 ± 5.4 seconds, r = 0.79 [95% CI 0.42-0.93], P = 0.001). In this cohort, older age was a predictor of longer (worse) K-D baseline time performance (age vs EyeLink-paired K-D: r = 0.70 [95% CI 0.24-0.90], P = 0.008; age vs K-D spiral-bound cards: r = 0.57 [95% CI 0.03-0.85], P = 0.04; age vs K-D tablet version: r = 0.59 [95% CI 0.06-0.86], P = 0.03) as well as prolonged ISI (r = 0.62 [95% CI 0.11-0.87], P = 0.02). Slower baseline K-D times were not associated with greater numbers of reported prior concussions. CONCLUSIONS: Rapid number-naming performance using the K-D at preseason baseline in this small cohort of collegiate ice hockey players is best correlated with ISI among eye movement-recording measures. Baseline K-D scores notably worsened with increasing age, but not with numbers of prior concussions in this small cohort. While these findings require further investigation by larger studies of contact and noncontact sports athletes, they suggest that duration of contact sports exposure may influence preseason test performance.

Validity of low-resolution eye-tracking to assess eye movements during a rapid number naming task: performance of the eyetribe eye tracker.

OBJECTIVE: To evaluate the performance of the EyeTribe compared to the EyeLink for eye movement recordings during a rapid number naming test in healthy control participants. BACKGROUND: With the increasing accessibility of portable, economical, video-based eye trackers such as the EyeTribe, there is growing interest in these devices for eye movement recordings, particularly in the domain of sports-related concussion. However, prior to implementation there is a primary need to establish the validity of these devices. One current limitation of portable eye trackers is their sampling rate (30-60 samples per second, or Hz), which is typically well below the benchmarks achieved by their research-grade counterparts (e.g., the EyeLink, which samples at 500-2000 Hz). METHODS: We compared video-oculographic measurements made using the EyeTribe with those of the EyeLink during a digitized rapid number naming task (the King-Devick test) in a convenience sample of 30 controls. RESULTS: EyeTribe had loss of signal during recording, and failed to reproduce the typical shape of saccadic main sequence relationships. In addition, EyeTribe data yielded significantly fewer detectable saccades and displayed greater variance of inter-saccadic intervals than the EyeLink system. CONCLUSION: Caution is advised prior to implementation of low-resolution eye trackers for objective saccade assessment and sideline concussion screening.

The effect of linguistic background on rapid number naming: implications for native versus non-native English speakers on sideline-focused concussion assessments.

OBJECTIVE: To determine if native English speakers (NES) perform differently compared to non-native English speakers (NNES) on a sideline-focused rapid number naming task. A secondary aim was to characterize objective differences in eye movement behaviour between cohorts. BACKGROUND: The King-Devick (KD) test is a rapid number-naming task in which numbers are read from left-to-right. This performance measure adds vision-based assessment to sideline concussion testing. Reading strategies differ by language. Concussion may also impact language and attention. Both factors may affect test performance. METHODS: Twenty-seven healthy  NNES and healthy NES performed a computerized KD test under high-resolution video-oculography.  NNES also performed a Bilingual Dominance Scale (BDS) questionnaire to weight linguistic preferences (i.e., reliance on non-English language(s)). RESULTS: Inter-saccadic intervals were significantly longer in  NNES (346.3 ± 78.3 ms vs. 286.1 ± 49.7 ms, p = 0.001), as were KD test times (54.4 ± 15.1 s vs. 43.8 ± 8.6 s, p = 0.002). Higher BDS scores, reflecting higher native language dominance, were associated with longer inter-saccadic intervals in  NNES. CONCLUSION: These findings have direct implications for the assessment of athlete performance on vision-based and other verbal sideline concussion tests; these results are particularly important given the international scope of sport. Pre-season baseline scores are essential to evaluation in the event of concussion, and performance of sideline tests in the athlete's native language should be considered to optimize both baseline and post-injury test accuracy.

A nonlinear generalization of the Savitzky-Golay filter and the quantitative analysis of saccades.

The Savitzky-Golay (SG) filter is widely used to smooth and differentiate time series, especially biomedical data. However, time series that exhibit abrupt departures from their typical trends, such as sharp waves or steps, which are of physiological interest, tend to be oversmoothed by the SG filter. Hence, the SG filter tends to systematically underestimate physiological parameters in certain situations. This article proposes a generalization of the SG filter to more accurately track abrupt deviations in time series, leading to more accurate parameter estimates (e.g., peak velocity of saccadic eye movements). The proposed filtering methodology models a time series as the sum of two component time series: a low-frequency time series for which the conventional SG filter is well suited, and a second time series that exhibits instantaneous deviations (e.g., sharp waves, steps, or more generally, discontinuities in a higher order derivative). The generalized SG filter is then applied to the quantitative analysis of saccadic eye movements. It is demonstrated that (a) the conventional SG filter underestimates the peak velocity of saccades, especially those of small amplitude, and (b) the generalized SG filter estimates peak saccadic velocity more accurately than the conventional filter.

Wearables for persons with blindness and low vision: form factor matters.

Based on statistics from the WHO and the International Agency for the Prevention of Blindness, an estimated 43.3 million people have blindness and 295 million have moderate and severe vision impairment globally as of 2020, statistics expected to increase to 61 million and 474 million respectively by 2050, staggering numbers. Blindness and low vision (BLV) stultify many activities of daily living, as sight is beneficial to most functional tasks. Assistive technologies for persons with blindness and low vision (pBLV) consist of a wide range of aids that work in some way to enhance one's functioning and support independence. Although handheld and head-mounted approaches have been primary foci when building new platforms or devices to support function and mobility, this perspective reviews potential shortcomings of these form factors or embodiments and posits that a body-centered approach may overcome many of these limitations.

Evaluating the efficacy of UNav: A computer vision-based navigation aid for persons with blindness or low vision.

UNav is a computer-vision-based localization and navigation aid that provides step-by-step route instructions to reach selected destinations without any infrastructure in both indoor and outdoor environments. Despite the initial literature highlighting UNav's potential, clinical efficacy has not yet been rigorously evaluated. Herein, we assess UNav against standard in-person travel directions (SIPTD) for persons with blindness or low vision (PBLV) in an ecologically valid environment using a non-inferiority design. Twenty BLV subjects (age = 38 ± 8.4; nine females) were recruited and asked to navigate to a variety of destinations, over short-range distances (<200 m), in unfamiliar spaces, using either UNav or SIPTD. Navigation performance was assessed with nine dependent variables to assess travel confidence, as well as spatial and temporal performances, including path efficiency, total time, and wrong turns. The results suggest that UNav is not only non-inferior to the standard-of-care in wayfinding (SIPTD) but also superior on 8 out of 9 metrics, as compared to SIPTD. This study highlights the range of benefits computer vision-based aids provide to PBLV in short-range navigation and provides key insights into how users benefit from this systematic form of computer-aided guidance, demonstrating transformative promise for educational attainment, gainful employment, and recreational participation.

Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development.

Goal: Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. Methods: We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1-3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). Results: For accuracy in the image center, all approaches had <±2.5 cm average error, except CoreML which had ±5.2-6.2 cm average error at 2-3 meters. In the periphery, all approaches were more inaccurate, with CoreML and IR_self having the highest average errors at ±41 cm and ±32 cm respectively. For usability, CoreML fared favorably with the lowest central processing unit usage, second lowest battery usage, highest field-of-view, and no specialized sensor requirements. Conclusions: We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV.

Speeded reaching movements around invisible obstacles.

We analyze the problem of obstacle avoidance from a Bayesian decision-theoretic perspective using an experimental task in which reaches around a virtual obstacle were made toward targets on an upright monitor. Subjects received monetary rewards for touching the target and incurred losses for accidentally touching the intervening obstacle. The locations of target-obstacle pairs within the workspace were varied from trial to trial. We compared human performance to that of a Bayesian ideal movement planner (who chooses motor strategies maximizing expected gain) using the Dominance Test employed in Hudson et al. (2007). The ideal movement planner suffers from the same sources of noise as the human, but selects movement plans that maximize expected gain in the presence of that noise. We find good agreement between the predictions of the model and actual performance in most but not all experimental conditions.

Training AI to Recognize Objects of Interest to the Blind and Low Vision Community.

Recent object detection models show promising advances in their architecture and performance, expanding potential applications for the benefit of persons with blindness or low vision (pBLV). However, object detection models are usually trained on generic data rather than datasets that focus on the needs of pBLV. Hence, for applications that locate objects of interest to pBLV, object detection models need to be trained specifically for this purpose. Informed by prior interviews, questionnaires, and Microsoft's ORBIT research, we identified thirty-five objects pertinent to pBLV. We employed this user-centric feedback to gather images of these objects from the Google Open Images V6 dataset. We subsequently trained a YOLOv5x model with this dataset to recognize these objects of interest. We demonstrate that the model can identify objects that previous generic models could not, such as those related to tasks of daily functioning - e.g., coffee mug, knife, fork, and glass. Crucially, we show that careful pruning of a dataset with severe class imbalances leads to a rapid, noticeable improvement in the overall performance of the model by two-fold, as measured using the mean average precision at the intersection over union thresholds from 0.5 to 0.95 (mAP50-95). Specifically, mAP50-95 improved from 0.14 to 0.36 on the seven least prevalent classes in the training dataset. Overall, we show that careful curation of training data can improve training speed and object detection outcomes. We show clear directions on effectively customizing training data to create models that focus on the desires and needs of pBLV.Clinical Relevance- This work demonstrated the benefits of developing assistive AI technology customized to individual users or the wider BLV community.

A Smart Service System for Spatial Intelligence and Onboard Navigation for Individuals with Visual Impairment (VIS4ION Thailand): study protocol of a randomized controlled trial of visually impaired students at the Ratchasuda College, Thailand.

BACKGROUND: Blind/low vision (BLV) severely limits information about our three-dimensional world, leading to poor spatial cognition and impaired navigation. BLV engenders mobility losses, debility, illness, and premature mortality. These mobility losses have been associated with unemployment and severe compromises in quality of life. VI not only eviscerates mobility and safety but also, creates barriers to inclusive higher education. Although true in almost every high-income country, these startling facts are even more severe in low- and middle-income countries, such as Thailand. We aim to use VIS4ION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation), an advanced wearable technology, to enable real-time access to microservices, providing a potential solution to close this gap and deliver consistent and reliable access to critical spatial information needed for mobility and orientation during navigation. METHODS: We are leveraging 3D reconstruction and semantic segmentation techniques to create a digital twin of the campus that houses Mahidol University's disability college. We will do cross-over randomization, and two groups of randomized VI students will deploy this augmented platform in two phases: a passive phase, during which the wearable will only record location, and an active phase, in which end users receive orientation cueing during location recording. A group will perform the active phase first, then the passive, and the other group will experiment reciprocally. We will assess for acceptability, appropriateness, and feasibility, focusing on experiences with VIS4ION. In addition, we will test another cohort of students for navigational, health, and well-being improvements, comparing weeks 1 to 4. We will also conduct a process evaluation according to the Saunders Framework. Finally, we will extend our computer vision and digital twinning technique to a 12-block spatial grid in Bangkok, providing aid in a more complex environment. DISCUSSION: Although electronic navigation aids seem like an attractive solution, there are several barriers to their use; chief among them is their dependence on either environmental (sensor-based) infrastructure or WiFi/cell "connectivity" infrastructure or both. These barriers limit their widespread adoption, particularly in low-and-middle-income countries. Here we propose a navigation solution that operates independently of both environmental and Wi-Fi/cell infrastructure. We predict the proposed platform supports spatial cognition in BLV populations, augmenting personal freedom and agency, and promoting health and well-being. TRIAL REGISTRATION: ClinicalTrials.gov under the identifier: NCT03174314, Registered 2017.06.02.

Motor learning reveals the existence of multiple codes for movement planning.

Coordinate systems for movement planning are comprised of an anchor point (e.g., retinocentric coordinates) and a representation (encoding) of the desired movement. One of two representations is often assumed: a final-position code describing desired limb endpoint position and a vector code describing movement direction and extent. The existence of movement-planning systems using both representations is controversial. In our experiments, participants completed reaches grouped by target location (providing practice for a final-position code) and the same reaches grouped by movement vector (providing vector-code practice). Target-grouped reaches resulted in the isotropic (circular) distribution of errors predicted for position-coded reaches. The identical reaches grouped by vector resulted in error ellipses aligned with the reach direction, as predicted for vector-coded reaches. Manipulating only recent movement history to provide better learning for one or the other movement code, we provide definitive evidence that both movement representations are used in the identical task.