GoPro Camera Research Articles

RISK OF INJURY COMPARISON BETWEEN REGULAR AND KNUCKLE PUSH-UP BASED ON KINEMATIC PARAMETER ANALYSIS

Nowadays, it is difficult to access physical exercise facilities because people spent most of their time at work. Therefore, physical exercises that could be done with less equipment and space are more likely needed, and a push-up is one of them. There are several kinds of push-up which two are regular push-up and knuckle push-up. Both of them differ in hand posture, which carries a different risk of injury. In this research, kinematic parameters of joints on both of the push-up method that was acquired from optical motion capture using 120 fps GoPro camera and six markers were compared to identify which method would lead to a higher risk of injury. From analyzing the elbow joints acceleration, it was observed that the maximum value of both the linear and angular acceleration of knuckle push-up was larger. This means that the elbow joints suffered more load during knuckle push-up, leading to a higher risk of injury.

A Hierarchical Approach for Traffic Sign Recognition Based on Shape Detection and Image Classification.

In recent years, the development of self-driving cars and their inclusion in our daily life has rapidly transformed from an idea into a reality. One of the main issues that autonomous vehicles must face is the problem of traffic sign detection and recognition. Most works focusing on this problem utilize a two-phase approach. However, a fast-moving car has to quickly detect the sign as seen by humans and recognize the image it contains. In this paper, we chose to utilize two different solutions to solve tasks of detection and classification separately and compare the results of our method with a novel state-of-the-art detector, YOLOv5. Our approach utilizes the Mask R-CNN deep learning model in the first phase, which aims to detect traffic signs based on their shapes. The second phase uses the Xception model for the task of traffic sign classification. The dataset used in this work is a manually collected dataset of 11,074 Taiwanese traffic signs collected using mobile phone cameras and a GoPro camera mounted inside a car. It consists of 23 classes divided into 3 subclasses based on their shape. The conducted experiments utilized both versions of the dataset, class-based and shape-based. The experimental result shows that the precision, recall and mAP can be significantly improved for our proposed approach.

A New Modified Video Solution System for Neuroendoscopic Procedures

Background and Aim: Today, neuroendoscopic surgery is gaining popularity because of its minimal damage to normal structures, fewer complications, and excellent clinical results. Using an endoscope and related instruments, surgeons can perform complex surgeries through small incisions, especially for minimally invasive spinal and brain surgeries. Neuroendoscopic systems are currently costly and not portable. Our new video solution is portable at a lower cost and can display and record images in 4K resolution. Methods and Materials/Patients: We modified the GoPro Hero 6 camera to serve our purpose. By detaching the original camera lens and its front part and replacing the removed parts with a new design, we made a C-mount camera that can connect to a standard C-mount coupler and various common scopes. For color correction, we used an IR-cut filter in front of the camera sensor. Results: By changing some parts of the camera and connecting it to a C-mount coupler and a scope lens, we made a small, portable neuroendoscope that displays and records images in clear, sharp, high resolution, with a high frame rate. Conclusion: The modified GoPro camera can be used as an alternative and unexpansive neuroendoscope system for education or treatment in medical centers in developing countries.

Deathlogging: GoPros as forensic media in accidental sporting deaths

This article develops the concept of ‘deathlogging’ as a complement to the more popular ‘lifelogging’ to describe how wearable cameras record fatal accidents, particularly among action sports participants. The article situates deathlogging in a history of media and communication theory interested in the relationships between life and death, and in particular the concept of forensic mediation to describe technologies capable of documenting and reconstructing accidents. The wearable GoPro camera is a camera of choice for action sports athletes to easily record and share things like BASE jumping to gain audience views and capital in the form of sponsorships. Representative examples are discussed and analyzed to demonstrate how fatal accidents transform the value of GoPro footage from social-economic capital into forensic or juridical evidence to reconstruct accidents, make sense of fatalities, and, in some instances, argue for legal culpability. The article offers deathlogging as a concept which can be applied to a variety of recording situations with different kinds of wearable cameras.

Work system factors affecting COVID-19 PPE use: A human factors approach to analysis of video recordings of emergency department clinical work

Background: The effectiveness of PPE in preventing self-contamination of healthcare workers (HCWs) and transmission of pathogens (airborne and contact) in the emergency department (ED) is highly dependent on consistent, appropriate use of and other interactions (eg, storing, cleaning, etc) with the PPE. Pre–COVID-19 studies focused primarily on individual HCW contributions to incorrect or suboptimal PPE use. We conducted an analysis of ED video recordings using a human-factors engineering framework (ie, The Systems Engineering Initiative for Patient Safety, SEIPS), to identify work-system–level contributions to inappropriate PPE usage by HCWs while they provide care in their actual clinical care environment. Methods: In total, 47 video sessions (each ~15 minute) were recorded between June 2020 and May 2021 using a GoPro camera in an 8-bed pod area, designated for persons under investigation (PUI) and confirmed COVID-19–positive patients, in an ED of a large, tertiary-care, academic medical center. These recordings captured a ‘landscape view’: 2 video cameras were set up to capture the entire ED pod area and HCWs as they provided care. A team with hemorrhagic fever expertise, infection prevention and control expertise, and ED expertise reviewed each video together and extracted data using a semistructured form. Results: Guided by the 5 components of the SEIPS work system model, (ie, task, physical environment, person, organization, tools and technology), multiple work system failure points influencing HCWs appropriate use of PPE were identified. For example, under the task component, HCWs were observed not doffing and donning in recommended sequence. Also, inconsistencies with COVID-19 status signage on a patient’s door and ambiguous labelling of work areas designated as clean (donning) and dirty (doffing) sites acted as a barrier to appropriate PPE use under the physical environment section. Conclusions: Human factors–based analysis of video recordings of actual ED work identified a variety of work system factors that impede appropriate or correct use of PPE by HCWs. Future efforts to improve appropriate PPE use should focus on eliminating or mitigating the effects of these work system factors.Funding: US CDCDisclosures: The authors gratefully acknowledge the CDC for funding this work. This material is based upon work supported by the Naval Sea Systems Command (under contract No. N00024-13-D-6400, Task Order NH076). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Naval Sea Systems Command (NAVSEA) or the US CDC.

Relationship between Eye Blink Frequency and Incremental Exercise among Young Healthy Men.

The aim of the study was to verify the correlation between the frequency of blinking and aerobic physical exercise. The research subjects were 13 healthy man aged 23.3 ± 1 year. Measurements of the blink rate and eye closure times were performed during a progressive aerobic test on a cycle ergometer. During the test, power was gradually increased every minute by 25 W, starting from 50 W. Data acquisition involved using a GoPro camera mounted to the helmet of the research subject. The test continued until the research subject refused to continue. The subjects did not know the goal of the test, in order to ensure objectivity and obtain natural results. The largest number of statistically significant differences was observed between the initial stages and 250 W, as well as between 250 W and 325 W. The analysis showed no significant differences in blink rate, eye closure time, and single blink time in terms of heart rate ranges. Regression models were also determined for eye closure time, blink frequency, and single blink time. The analysis showed that blink frequency and eye closure time were determined by a group of factors (the value of cycle ergometer load power, heart rate, body weight, adipose tissue mass, fat-free mass, and total body water and body surface ratio).

A Comparative Study of Various Edge Detection Techniques for Underwater Images

Nowadays, underwater image identification is a challenging task for many researchers focusing on various applications, such as tracking fish species, monitoring coral reef species, and counting marine species. Because underwater images frequently suffer from distortion and light attenuation, pre-processing steps are required in order to enhance their quality. In this paper, we used multiple edge detection techniques to determine the edges of the underwater images. The pictures were pre-processed with the use of specific techniques, such as enhancement processing, Wiener filtering, median filtering and thresholding. Coral reef pictures were used as a dataset of underwater images to test the efficiency of each edge detection method used in the experiment. All coral reef image datasets were captured using an underwater GoPro camera. The performance of each edge detection technique was evaluated using mean square error (MSE) and peak signal to noise ratio (PSNR). The lowest MSE value and the highest PSNR value represent the best quality of underwater images. The results of the experiment showed that the Canny edge detection technique outperformed other approaches used in the course of the project.

A Machine Learning Classifier for Detection of Physical Activity Types and Postures During Free-Living

Introduction:Accelerometer-based measurements of physical activity types are commonly used to replace self-reports. To advance the field, it is desirable that such measurements allow accurate detection of key daily physical activity types. This study aimed to evaluate the performance of a machine learning classifier for detecting sitting, standing, lying, walking, running, and cycling based on a dual versus single accelerometer setups during free-living.Methods:Twenty-two adults (mean age [SD, range] 38.7 [14.4, 25–68] years) were wearing two Axivity AX3 accelerometers positioned on the low back and thigh along with a GoPro camera positioned on the chest to record lower body movements during free-living. The labeled videos were used as ground truth for training an eXtreme Gradient Boosting classifier using window lengths of 1, 3, and 5 s. Performance of the classifier was evaluated using leave-one-out cross-validation.Results:Total recording time was ∼38 hr. Based on 5-s windowing, the overall accuracy was 96% for the dual accelerometer setup and 93% and 84% for the single thigh and back accelerometer setups, respectively. The decreased accuracy for the single accelerometer setup was due to a poor precision in detecting lying based on the thigh accelerometer recording (77%) and standing based on the back accelerometer recording (64%).Conclusion:Key daily physical activity types can be accurately detected during free-living based on dual accelerometer recording, using an eXtreme Gradient Boosting classifier. The overall accuracy decreases marginally when predictions are based on single thigh accelerometer recording, but detection of lying is poor.

The effects of learning with various noise on Gait Kinematics in 3-to-5-year-old children: a randomized controlled trial

BackgroundLack of the neuromuscular control during locomotion in the knee joint leads to an increased risk of anterior cruciate ligament (ACL) injury in children. Hence, we aimed to explore the effects of a repetitive, model-oriented, and self-organized approach on lower limb kinematics during gait in children.MethodsIn randomized controlled trial, 36 children with 4 ± 0.79 years of age from the children gym were randomly (a lottery method) allocated into three groups, including (1) the model-oriented (n = 10), (2) Differential Learning (n = 11), and (3) control (n = 10) groups. Kinematic data of hip, knee, and ankle joints in the sagittal plane were recorded by a GoPro camera at the moments of heel-ground contact and toe-off the ground before and after a 6-week intervention (two sessions per week).ResultsThe results indicate a 35% post-intervention increase of ankle dorsiflexion (95% CI: − 5.63 _ − 0.96) in the moment of heel-ground contact in the model-oriented group; however, knee flexion (95% CI: − 1.05 _ 8.34) and hip flexion (95% CI: 3.01 _ 11.78) were respectively decreased by 20% and 20%. After the intervention, moreover, ankle plantar flexion (95% CI: − 9.18 _ − 2.81) and hip extension (95% CI: − 12.87 _ − 3.72) have respectively increased by 37% and 37%, while knee flexion (95% CI: 3.49 _ 11.30) showed a %16 decrease in the moment of toe off the ground. As for the Differential Learning group, ankle dorsiflexion (95% CI: − 5.19 _ − 1.52) increased by 33%, and knee (95% CI: 0.60 _ 5.76) and hip flexion (95% CI: 2.15 _ 7.85) respectively decreased by 17% and 17% at the moment of the heel-ground contact following the intervention. At toe lifting off the ground, the plantar flexion (95% CI: − 7.77 _ − 2.77) increased by 35%, knee flexion (95% CI: 2.17 _ 7.27) decreased to 14%, and hip extension (95% CI: − 9.98 _ − 4.20) increased by %35 following the intervention for the Differential Learning group subjects. Based on the results obtained from the one-way ANOVA, there was a significant difference between these groups and the control group in all kinematic gait variables (p ≤ 0.05). However, no statistically significant differences were found between the two experimental groups.ConclusionsThe results implied that the model-oriented repetitive and the self-organized Differential Learning approach were both appropriate to alter the kinematic gait pattern in the 3–5-year-old children. Previous research has almost exclusively recommended a model-oriented approach to change kinematic patterns and preventing non-contact motor injuries. However, the present study showed that the Differential Learning approach can help children to achieve the same goal by continuously changing environments and stimulating challenges.Trial registration: Current Controlled Trials using the IRCT website with ID number of, IRCT20130109012078N5 “Prospectively registered” at 14/5/2021.

Behavioral responses of blue-winged teal and northern shoveler to unmanned aerial vehicle surveys.

Unmanned aerial vehicles (UAVs) have become a popular wildlife survey tool. Most research has focused on detecting wildlife using UAVs with less known about behavioral responses. We compared the behavioral responses of breeding blue-winged teal (Spatula discors) (n = 151) and northern shovelers (Spatula clypeata) (n = 46) on wetlands flown over with a rotary DJI Matrice 200 quadcopter and control wetlands without flights. Using a GoPro camera affixed to a spotting scope, we conducted focal individual surveys and recorded duck behaviors for 30 minutes before, during, and 30 minutes after UAV flights to determine if ducks flushed or changed in specific activities. We also conducted scan surveys during flights to examine flushing and movement on the entire wetland. Between 24 April and 27 May 2020, we conducted 42 paired (control and flown) surveys. Both teal and shovelers increased proportion of time engaged in overhead vigilance on flown wetlands from pre-flight to during flight (0.008 to 0.020 and 0.006 to 0.032 of observation time, respectively). Both species left the wetland more frequently during flights than ducks on control wetlands. Despite similarities between species, we observed marked differences in time each species spent on active (e.g., feeding, courtship, swimming), resting, and vigilant behaviors during flights. Overall, teal became less active during flights (0.897 to 0.834 of time) while shovelers became more active during this period (0.724 to 0.906 of time). Based upon scan surveys, ducks flushed in 38.1% of surveys while control wetlands only had a single (2.4%) flush during the flight time. We found launch distance was the most important predictor of whether ducks swam for cover or away from the UAV which could result in inaccurate counts. Ducks appear aware of UAVs during flights, but minimal behavioral shifts suggest negative fitness consequences are unlikely.

Reducing Spin on a High Altitude Balloon

The goal of this experiment was to reduce spin on an unmanned balloon as the altitude increases. This problem had been discovered after the initial flight, where the rotation of the Go-Pro camera was nearly sickening. After more research, it was found that every flight had the same lack of stability and high levels of rotation. The goal was then decided to try and reduce the spin of the payload so that stable pictures and video could be achieved. If there was a stable video going the whole way up, then the goal was considered complete, however, a gyroscope was included in each flight to find the reduction of spin in the payload.

A mechanistic approach to evaluate the fatigue life of inverted pavements

Fatigue cracking is one of the most critical failure types in flexible pavements under the application of repeated wheel loads. The application of vehicular load induces micro-cracks with each application eventually causing macro-cracks and failure. The chances of crack propagation multiply if a brittle cement-treated base layer lies underneath, as in the case of an inverted pavement. This study investigates the fatigue cracking in inverted pavements considering the effect of the brittleness of an underlying cemented layer. Several specimens were manufactured and tested in a wheel tracking environment while crack initiation and propagation were carefully monitored using a GoPro camera. A mechanics-based methodology has been developed to calculate the critical horizontal tensile strain at the bottom of the hot mix asphalt surface layer, which has been related to fatigue life by a fatigue prediction model. It is observed that the laboratory results are in close correlation with the predicted fatigue life. The developed approach has also been successfully applied to real pavements, constituting an important development in fatigue life prediction in inverted pavements.

Efficacy of ethylene oxide-sterilized waterproof cases for handheld cameras as sterile barriers for intraoperative imaging and recording.

To evaluate the efficacy of ethylene oxide (EtOH) sterilization of 4 different waterproof camera cases and the ability of those sterilized cases to maintain a sterile barrier for intraoperative camera use. 3 action cameras, 1 smartphone, and associated waterproof cases. Cases were inoculated by immersion in medium containing Staphylococcus pseudintermedius, Escherichia coli, and Pseudomonas aeruginosa and then manually cleaned and subjected to EtOH sterilization. Cameras were disinfected, loaded into sterile cases, and sterilely operated for 2 hours. Samples were collected from cases after inoculation, EtOH sterilization, camera loading, and 1 and 2 hours of operation and from all cameras after 2 hours of operation. Procedures were repeated twice, followed by an additional challenge round wherein cameras were purposefully contaminated prior to loading. All samples underwent bacterial culture. All cases were successfully sterilized, and loading of nonsterile cameras into sterile cases caused no contamination when cameras had been disinfected beforehand. Nonpathogenic environmental contaminants were recovered from 6 of 64 culture samples and 2 of 4 room samples. During the challenge round, only the postload sample for 1 case yielded E coli, suggesting sterile glove contamination; however, postload, 1-hour, and 2-hour samples for the GoPro case yielded E coli and S pseudintermedius, suggesting major contamination. Results suggested that the evaluated cases can be safely sterilized with EtOH and used for image acquisition by aseptically prepared surgeons when cameras are disinfected prior to loading. Except for the GoPro camera, camera use did not jeopardize sterile integrity.

Surface wave measurements with IoT image processing

This study develops two different approaches to perform temporal and spatial measurements of surface wave profile for experimental studies in transparent wave flumes. Both are based on image acquisition and processing with an Internet of Things (IoT) system consisting of three sets of GoPro camera cum Raspberry Pi connected wirelessly together in a local LAN. The first approach uses advanced edge algorithms with perspective transformation of the multiple cameras for the detection, while the second approach adopts Convolutional Neural Network (CNN) algorithms instead with training of the processed image data using information from additional discrete probes installed. Their accuracy is assessed under a range of experimental conditions of regular and irregular waves with different wave heights and periods, based on metrics that consist of the average errors of the predicted water surface profile as well as position errors for wave crests and troughs. The effects on the measurement accuracy due to the image acquisition frequency, camera resolution and camera location are also investigated. The results show that higher wave steepnesses generally lead to larger detection errors, and measurements for irregular waves are also more challenging. In addition, positioning the cameras closer to the wave flume sidewalls yields better detection results as expected, particularly in resolving wave crests and troughs, although the field of view narrows at the same time. However, higher video frequencies and camera resolutions might not necessarily improve the accuracy contrary to common expectation due to jaggedness in the image processing. Overall, both approaches are shown to be viable for the measurement of wave profile in the laboratory. The first approach is more straight forward in terms of implementation, and it performs well for regular wave conditions. The second approach requires more complex training of the neural networks, but its accuracy is significantly higher particularly for irregular waves.

Assessment of chest compression interruptions during advanced cardiac life support

AimTo identify potentially avoidable factors responsible for chest compression interruptions and to evaluate the influence of chest compression fraction on achieving return of spontaneous circulation and survival to hospital discharge. MethodsIn this prospective observational study, each resuscitation managed by mobile medical teams from August 1st, 2016, to August 1st, 2018 was video recorded using a body-mounted GoPro camera. The duration of all chest compression interruptions was recorded and chest compression fraction was calculated. All actions causing an interruption of at least 10 s were analyzed. ResultsTwo hundred and six resuscitations of both in- and out-of-hospital cardiac arrest patients were analysed. In total 1867 chest compression interruptions were identified. Of these, 623 were longer than 10 s in which a total of 794 actions were performed. In 4.3% of the registered pauses, cardiopulmonary resuscitation was interrupted for more than 60 s. The most performed actions during prolonged interruptions were rhythm/pulse checks (51.6%), installation/use of mechanical chest compression devices (11.1%), cardiopulmonary resuscitation provider switches (6.7%) and ETT placements (6.2%). No statistically significant relationship was found between chest compression fraction and return of spontaneous circulation or survival. ConclusionThe majority of chest compression interruptions during resuscitation were caused by prolonged rhythm checks, cardiopulmonary resuscitation provider switches, incorrect use of mechanical chest compression devices and ETT placement. No association was found between chest compression fraction and return of spontaneous circulation, nor an influence on survival. This was presumably caused by the high baseline chest compression fraction of >86%.

Three experiments on the Einstein’s lift

We propose a didactic model of Einstein's lift used to show the physics in a freefalling frame of reference. We discuss three experiments in Einstein's lift: the spring-mass system, the two repelling magnets system and the pendulum oscillations in free fall. Measurements are carried out through analysing videos acquired using a digital camera by means of open-access video analysis software which allows to describe the motion in both the inertial and moving frames of reference. We also show some videos edited with the software Adobe After Effects which enable us to see what happens in a freefalling frame of reference, and a video acquired by a GoPro camera falling integral with the lift. The topic, the accessibility of the experiments and the level of analysis are appropriate for an undergraduate classical mechanics course.

Evaluating the Accuracy and Reliability of Bicycle GPS Devices

<div class="section abstract"><div class="htmlview paragraph">Every day in the United States, an average of approximately two cyclists die in bicycle accidents. Sometimes, forensic engineers are asked to reconstruct these accidents. These cyclists may use bicycle GPS devices to record important data, which they use to monitor their riding activities. By analyzing this data, many questions can be answered regarding various parameters such as speed, position, and riding behavior of the bicyclist.</div><div class="htmlview paragraph">The goal of this study was to analyze the accuracy of the GPS position and speed data. For this study, four different bicycle GPS devices (one of which was paired with a magnetometer Garmin Bicycle Speed Sensor), a GoPro camera equipped with GPS, and a smartphone recording to Strava, were mounted on a bicycle. The bicycle was ridden in an approximately straight line (back and forth), and then around a building, to measure positional and speed accuracy. Additionally, the bicycle was ridden in a straight line, then decelerated to a complete stop for varied durations, and then accelerated forward. This was done to see if the retrieved data showed the bicycle coming to a complete stop, or if the GPS averaged a few data points showing that the rider never came to a stop. Furthermore, the bicycle was stopped at a specific location for a certain duration and the GPS drift of each device was studied. </div><div class="htmlview paragraph">Using VBOX 3i RTK DGPS positional data as the reference, test data revealed that all six bicycle test devices had relative error in positional and speed data. The Garmin Edge 530 had an average speed error of 10.83% and positional error of 21.78 ft. The Garmin Edge 1000 (BSS) had an average speed error of 4.71% and positional error of 15.2 ft. The Lezyne Mega XL had an average speed error of 3.5% and positional error of 4.82 ft. The Wahoo ELEMNT Bolt had an average speed error of 3.53% and a positional error of 10.46 ft. The Strava app had a positional error of 11.45 ft. The GoPro Hero5 had an average speed error of 5.05% and a positional error of 4.79 ft.</div></div>

Assessing the Behavioural Responses of Small Cetaceans to Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs), or drones, have recently emerged as a relatively affordable and accessible method for studying wildlife. Vertical Take-off and Landing (VTOL) UAVs are appropriate for morphometric, behavioural, abundance and demographic studies of marine mammals, providing a stable, nonintrusive and highly manoeuvrable platform. Previous studies using VTOL UAVs have been conducted on various marine mammal species, but specific studies regarding behavioural responses to these devices are limited and scarce. The aim of this study was to evaluate the immediate behavioural responses of common (Delphinus delphis) and bottlenose (Tursiops truncatus) dolphins to a VTOL UAV flown at different altitudes. A multirotor (quadcopter) UAV with an attached GoPro camera was used. Once a dolphin group was located, the UAV was flown at a starting height of 50 m directly above the group, subsequently descending 5 m every 30 s until reaching 5 m. We assessed three behavioural responses to a VTOL UAV at different heights: (i) direction changes, (ii) swimming speed and (iii) diving. Responses by D. delphis (n = 15) and T. truncatus (n = 10) groups were analysed separately. There were no significant responses of T. truncatus to any of the studied variables. For D. delphis, however, there were statistically significant changes in direction when the UAV was flown at a height of 5 m. Our results indicate that UAVs do not induce immediate behavioural responses in common or bottlenose dolphins when flown at heights > 5 m, demonstrating that the use of VTOL UAVs to study dolphins has minimal impact on the animals. However, we advise the use of the precautionary principle when interpreting these results as characteristics of this study site (e.g., high whale-watching activity) may have habituated dolphins to anthropogenic disturbance.

Supine lying center of pressure movement characteristics as a predictor of normal developmental stages in early infancy.

Absent or abnormal fidgety movements in young infants are associated with subsequent diagnoses of developmental disorders such as cerebral palsy. The General Movement Assessment (GMA) is a qualitative clinical tool to visually identify infants with absent or abnormal fidgety movements associated with developmental stage, yet no quantitative measures exist to detect fidgety activity. To determine whether a correlation exists between quantitative Center of Pressure (CoP) measurements during supine lying and age. Twenty-four healthy full-term infants participated in the Institutional Review Board-approved study. Participants were placed supine in view of a GoPro camera on an AMTI force plate for two minutes. Spontaneous movements were evaluated by three trained raters using the GMA. Traditional CoP parameters (range, total path length, mean velocity, and mean acceleration of resultant CoP) were assessed, and complexity of each of the resultant CoP variables (location, velocity, and acceleration) was calculated by sample entropy. Linear regression with Pearson correlation was performed to assess the correlations between the CoP parameters and adjusted age. Nineteen infants were deemed fidgety per the GMA and were included in further analyses. All Sample entropy measures and range of resultant CoP had significant correlations with adjusted age (p< 0.05). Sample entropy of resultant CoP decreased with increasing age while range of resultant CoP increased with increasing age. The results suggest that complexity of CoP and range of CoP are good predictors of age in typical developing infants during the fidgety period. Therefore, an approach using these parameters should be explored further as a quantifiable tool to identify infants at risk for neurodevelopmental impairment.

An exploration of the navigational behaviours of people who use wheeled mobility devices in unfamiliar pedestrian environments

PurposeThis paper explores the challenges that people who use wheeled mobility devices face navigating unfamiliar pedestrian environments. The intent is to understand their decisions during the planning and travel phases and to compare these decisions and experiences between mobility device users. MethodsFourteen mobility device users (4 manual wheelchair, 6 power wheelchair, and 4 scooter users) completed surveys that captured data about socio-economic and disability status, mobility device skills and confidence, and wayfinding abilities. As part of a wheeling interview, participants planned trips to three destinations in an unfamiliar urban setting. They wore a GoPro camera affixed to their head and carried a global positioning system device as they wheeled to each destination. During each trip, participants answered questions regarding their decisions and experiences. At the end of each route, participants rated the physical and mental demand of the trip and rated their own performance using the NASA-TLX questionnaire. They also completed wayfinding skills tests of their spatial orientation and ability to estimate distance and slope. Transcripts of the videos were coded and analyzed using interpretive description. Spatial and qualitative data were then uploaded into a geographical information system to identify patterns in decision making and experiences and compare across mobility devices. ResultsThe findings highlight the complex and dynamic challenges faced by wheeled mobility device users and the implications on their mobility. The findings emphasize the relationship between the individual, the mobility device, and the environment to shape navigational experiences. Manual wheelchair users appeared to struggle more with navigation because accessibility issues diverted their attention away from maintaining orientation and heading. ConclusionsWheeled mobility device users face challenges navigating unfamiliar environments that make reaching destinations difficult which may deter community participation. Environments that incorporate their diverse and unique requirements should be considered in urban design and research.