The crank angle is an important outcome in biomechanical analyses of cycling. Wireless inertial and magnetic measurement systems are unobtrusive and have the potential to measure crank angles more advantageously than ergometers, encoders or cameras. However, magnetic field disturbances and large centripetal accelerations during pedaling introduce tracking errors. The aim of this study was to validate two magnetometer-free sensor-to-body frame alignment methods for tracking the bicycle crank angle using wireless inertial and magnetic measurement systems. A passive complementary filter is presented for tracking the crank angle using an inertial and magnetic measurement system mounted on the bicycle frame and another on the crank arm. Sensor-to-body frame alignment is performed for both inertial and magnetic measurement systems using functional calibration techniques that do not require magnetometer measurements. The filter also performs dynamic tracking of the crank arm inertial and magnetic measurement system without magnetometer data by exploiting domain constraints and compensating for centripetal accelerations. The filter was validated at a slow, medium and fast pedaling cadence using stereophotogrammetry. The filter produced absolute errors of 1.3° ± 0.9° or less in all three tests. In contrast, large and variable absolute errors (11.6° ± 7.6°, 14.2° ± 10.7° and 14.0° ± 10.2°, respectively) were found with a standard passive complementary filter using a traditional static pose calibration that relies on magnetometer data. The proposed filter operated with low and consistent errors despite the presence of magnetic interferences, whereas traditional magnetometer-based approaches produced unacceptable results. This study contributes toward the ultimate goal of outdoor cycling analysis using inertial and magnetic measurement system technology by accomplishing magnetometer-free frame alignment and centripetal acceleration compensation when tracking crank angles.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a worldwide prevalence of 1–2%. In low-resource environments, in particular, early identification and diagnosis is a significant challenge. Therefore, there is a great demand for ‘language-free, culturally fair’ low-cost screening tools for ASD that do not require highly trained professionals. Electroencephalography (EEG) has seen growing interest as an investigational tool for biomarker development in ASD and neurodevelopmental disorders. One of the key challenges is the identification of appropriate multivariate, next-generation analytical methodologies that can characterise the complex, nonlinear dynamics of neural networks in the brain, mindful of technical and demographic confounders that may influence biomarker findings. The aim of this study was to evaluate the robustness of recurrence quantification analysis (RQA) as a potential biomarker for ASD using a systematic methodological exploration of a range of potential technical and demographic confounders.

Objectives: To investigate the influence of ventilation and ventilation-compression synchronization on compression force and sternal displacement during simulated neonatal cardiopulmonary resuscitation (NCPR) on an infant manikin.Methods: Five Neonatal Resuscitation Program trained clinicians were recruited to perform simulated NCPR on an infant manikin using two-finger (TF) and two-thumb (TT) compression, with synchronous and asynchronous ventilation, as well as without ventilation. The sternal displacement and force were recorded and analyzed.Results: Synchronous ventilation and compression yielded sternal displacements and forces in the range of 22.8-32.4mm and 15.0-29.8 N, respectively, while asynchronous ventilation and compression produced depths and forces in the range of 21.2-32.4mm and 14.0-28.8 N, respectively.Conclusions: Ventilation exerts a significant influence on sternal displacement and force during simulated NCPR, regardless of the compression method used. Ventilation-compression synchronization, however, is only significant during TF compression with lower compression forces measured during synchronous ventilation than in asynchronous ventilation. This occurs for two reasons: (i) the strong influence of ventilation forces on the lower magnitude compression forces produced during TF compression relative to TT compression and (ii) in asynchronous ventilation, compression and ventilation may occur simultaneously, with inflation and deflation providing an opposing force to the applied compression force.

Dehydration resulting from acute diarrhea is one of the leading causes of infant mortality in the developing world. Safe assessment of an infant's hydration level is essential to determine appropriate clinical intervention strategies. However, clinical hydration scales, which are the current gold standard for non-invasive hydration assessment, are often unreliable in lower resource settings. This study presents the development and testing of non-invasive, optical sensors for the objective assessment of dehydration based on the quantitative measurement of skin recoil time, capillary refill time and skin temperature. The results obtained have demonstrated the basic feasibility of using optical sensors for the objective assessment of dehydration. However, several challenges must be overcome before these sensors can be applied in a clinical setting.

BACKGROUND:Pre-eclampsia is one of the leading causes of maternal death and morbidity in low-resource countries due to delays in case identification and a shortage of health workers trained to manage the disorder. Pre-eclampsia Integrated Estimate of RiSk (PIERS) on the Move (PotM) is a low cost, easy-to-use, mobile health (mHealth) platform that has been created to aid health workers in making decisions around the management of hypertensive pregnant women. PotM combines two previously successful innovations into a mHealth app: the miniPIERS risk assessment model and the Phone Oximeter.OBJECTIVE:The aim of this study was to assess the usability of PotM (with mid-level health workers) for iteratively refining the system.METHODS:Development of the PotM user interface involved usability testing with target end-users in South Africa. Users were asked to complete clinical scenario tasks, speaking aloud to give feedback on the interface and then complete a questionnaire. The tool was then evaluated in a pilot clinical evaluation in Tygerberg Hospital, Cape Town.RESULTS:After ethical approval and informed consent, 37 nurses and midwives evaluated the tool. During Study 1, major issues in the functionality of the touch-screen keyboard and date scroll wheels were identified (total errors n=212); during Study 2 major improvements in navigation of the app were suggested (total errors n=144). Overall, users felt the app was usable using the Computer Systems Usability Questionnaire; median (range) values for Study 1 = 2 (1-6) and Study 2 = 1 (1-7). To demonstrate feasibility, PotM was used by one research nurse for the pilot clinical study. In total, more than 500 evaluations were performed on more than 200 patients. The median (interquartile range) time to complete an evaluation was 4 min 55 sec (3 min 25 sec to 6 min 56 sec).CONCLUSIONS:By including target end-users in the design and evaluation of PotM, we have developed an app that can be easily integrated into health care settings in low- and middle-income countries. Usability problems were often related to mobile phone features (eg, scroll wheels, touch screen use). Larger scale evaluation of the clinical impact of this tool is underway.

In-field tracking of crank angles is important for analyzing outdoor cycling biomechanics, but current encoder-based methods are expensive and time-consuming. Inertial and magnetic measurement systems (IMMSs) have the potential for minimally invasive crank angle tracking, although errors due to magnetic interference and static calibration hinder performance. This paper presents a nonlinear complimentary filter, called the constrained rotational acceleration and kinematics (CRANK) filter, which estimates crank angles without magnetometer measurements or a static calibration for the crank arm IMMS. The CRANK filter removes drift errors by exploiting constraints on the kinematics of the crank arm relative to the bicycle frame. Three 5 min cycling tests were conducted using stereophotogrammetry and two IMMSs; a slow (similar to 80 r/min) and medium (90 r/min) cadence test on a level surface and a fast cadence test (100 r/min) with the bicycle inclined at 20 degrees to the ground. A novel two-segment methodology for collecting ground truth data with an optical motion capture system is presented. We also provide analysis of CRANK filter performance for simulated outdoor dynamics (lateral tilt and roll). The CRANK filter achieved absolute errors (AEs) of 0.9 +/- 0.6 degrees, 1.7 +/- 1.4 degrees, and 1.8 +/- 1.2 degrees for the slow, medium, and fast tests, outperforming a commercial Kalman filter that produced AEs of similar to 10 degrees. Under simulated outdoor conditions the CRANK filter was only slightly less accurate (AEs approximate to 3 degrees). The CRANK filter is shown to be accurate, drift-free, easy to implement and robust against magnetic disturbances, sensor positioning, bicycle inclination, and bicycle frame dynamics.

We present a study evaluating two respiratory rate estimation algorithms using videos obtained from placing a finger on the camera lens of a mobile phone. The two algorithms, based on Smart Fusion and empirical mode decomposition (EMD), consist of previously developed signal processing methods to detect features and extract respiratory induced variations in photoplethysmographic signals to estimate respiratory rate. With custom-built software on an Android phone, photoplethysmographic imaging videos were recorded from 19 healthy adults while breathing spontaneously at respiratory rates between 6 to 32 breaths/min. Signals from two pulse oximeters were simultaneously recorded to compare the algorithms' performance using mobile phone data and clinical data. Capnometry was recorded to obtain reference respiratory rates. Two hundred seventy-two recordings were analyzed. The Smart Fusion algorithm reported 39 recordings with insufficient respiratory information from the photoplethysmographic imaging data. Of the 232 remaining recordings, a root mean square error (RMSE) of 6 breaths/min was obtained. The RMSE for the pulse oximeter data was lower at 2.3 breaths/min. RMSE for the EMD method was higher throughout all data sources as, unlike the Smart Fusion, the EMD method did not screen for inconsistent results. The study showed that it is feasible to estimate respiratory rates by placing a finger on a mobile phone camera, but that it becomes increasingly challenging at respiratory rates greater than 20 breaths/min, independent of data source or algorithm tested.

The clinical assessment of dehydration is highly subjective and requires experienced and highly trained clinical personnel. At present no objective method for quantitatively determining an individual's dehydration status exists. The aim of this study is to address this deficiency by presenting the development and testing of a novel diagnostic tool for dehydration detection based on infrared spectrometry. Laboratory testing and two clinical studies were conducted to evaluate the efficacy of the device in both adults and infants. The results were promising for the infant study with a clear trend exhibited. However, a number of challenges must be overcome before this sensor can be applied in a clinical setting.

As wireless motion sensors become more compact and robust, new opportunities emerge to develop wearable measurement technologies for in-field sports analysis. This paper presents a nonlinear complimentary filter for tracking 3-D hip joint angles during cycling using inertial and magnetic measurement systems (IMMSs). The filter utilizes a novel method of dynamic acceleration compensation in the sensor frame based on the assumption of pendulum motion of the thigh around the hip joint center. A dynamic calibration is proposed in which the center of rotation of the thigh IMMS can be estimated during a functional hip movement in standing. Validation results from a gold-standard optical system showed that the filter IMMS tracking is drift-free with mean absolute errors of less than 3° for all IMMS axes combined at low, medium, and high pedaling speeds. Hip angles were also validated using the Vicon biomechanical model for standing and sitting calibration poses as well as true and normalized soft-tissue-artefact (STA). The best mean absolute errors for the sagittal, frontal, and coronal planes were 0.8°, 6.7°, and 2.2°, respectively. Variability due to calibrations and STA ranged from 1.4° to 8.1°. This demonstrates the high accuracies possible for IMMS tracking using algorithms designed for specific sports despite larger errors due to modeling.

Objectives: To evaluate the performance of a real-time feedback algorithm for chest compression (CC) during cardiopulmonary resuscitation (CPR), which provides accurate estimation of the CC depth based on dual accelerometer signal processing, without assuming full CDC. Also, to explore the influence of incomplete chest decompression (CDC) on the CC depth estimation performance.Methods: The performance of a real-time feedback algorithm for CC during CPR was evaluated by comparison with an offline algorithm using adult CPR manikin CC data obtained under various conditions.Results: The real-time algorithm, using non-causal baselining, delivered comparable CC depth estimation accuracy to the offline algorithm on both soft and hard back support surfaces. In addition, for both algorithms incomplete CDC led to underestimation of the CC depth.Conclusions: CPR feedback systems which utilize an assumption of full CDC may be unreliable especially in long duration CPR events where rescuer fatigue can strongly influence CC quality. In addition, these systems may increase the risk of thoracic and abdominal injury during CPR since rescuers may apply excessive compression forces due to underestimation of the CC depth when incomplete CDC occurs. Hence, there is a strong need for CPR feedback systems to accurately measure CDC in order to improve their clinical effectiveness. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

In this study the potential of a Laser Doppler Vibrometer (LDV) was tested as a non-contact sensor for the classification of heart sounds. Of the twenty participants recorded using the LDV, five presented with Aortic Stenosis (AS), three were healthy and twelve presented with other pathologies. The recorded heart sounds were denoised and segmented using a combination of the Electrocardiogram (ECG) data and the complexity of the signal. Frequency domain features were extracted from the segmented heart sound cycles and used to train a K-nearest neighbor classifier. Due to the small number of participants, the classifier could not be trained to differentiate between normal and abnormal participants, but could successfully distinguish between participants who presented with AS and those who did not. A sensitivity of 80 % and a specificity of 100 % were achieved a test dataset.

Clinical guidelines, such as the Integrated Management of Childhood Illness (IMCI), are used worldwide to support community health workers in the assessment of severely ill children. These guidelines are distributed in paper form, complicating their use at the point-of-care. We have developed a framework for building advanced clinical guideline applications for the Android mobile phone OS. The framework transfers clinical guidelines into a flexible and interactive electronic format using an XML interpreter. The resulting application supports intuitive navigation of guidelines while assessing the patient, easy integration of patient management tools, and logging of performed assessments and treatments. The novel approach transforms clinical guidelines from a mere paper dictionary into a working tool that integrates into the daily workflow of community health workers and simplifies their task at the care and administrative levels.

We propose a communication library, ShareVitalSigns, for the standardized exchange of vital sign information between health applications running on mobile platforms.The library allows an application to request one or multiple vital signs from independent measurement applications on the Android OS. Compatible measurement applications are automatically detected and can be launched from within the requesting application, simplifying the work flow for the user and reducing typing errors. Data is shared between applications using intents, a passive data structure available on Android OS. The library is accompanied by a test application which serves as a demonstrator.The secure exchange of vital sign information using a standardized library like ShareVitalSigns will facilitate the integration of measurement applications into diagnostic and other high level health monitoring applications and reduce errors due to manual entry of information.

We present a study investigating the suitability of a respiratory rate estimation algorithm applied to photoplethysmographic imaging on a mobile phone. The algorithm consists of a cascade of previously developed signal processing methods to detect features and extract respiratory induced variations in photoplethysmogram signals to estimate respiratory rate. With custom-built software on an Android phone (Camera Oximeter), contact photoplethysmographic imaging videos were recorded using the integrated camera from 19 healthy adults breathing spontaneously at respiratory rates between 6 and 40 breaths/min. Capnometry was simultaneously recorded to obtain reference respiratory rates. Two hundred and ninety-eight Camera Oximeter recordings were available for analysis. The algorithm detected 22 recordings with poor photoplethysmogram quality and 46 recordings with insufficient respiratory information. Of the 232 remaining recordings, a root mean square error of 5.9 breaths/min and a median absolute error of 2.3 breaths/min was obtained. The study showed that it is feasible to estimate respiratory rates by placing a finger on a mobile phone camera, but that it becomes increasingly challenging at respiratory rates higher than 20 breaths/min.

Pleural effusion is one of the most widespread respiratory diseases in the world. Current diagnostic techniques include a combination of medical history and x-ray or CT scan imaging of the chest. However, these techniques are expensive and impractical in resource limited settings. We propose a new method based on sound transmission into the respiratory system through the chest wall. To evaluate this technique, a sine sweep signal with a frequency range between 100 Hz and 1000 Hz was transmitted into a phantom model of the human lungs capable of simulating healthy and effused conditions. The frequency response of the model under both conditions was computed and compared to evaluate the diagnostic performance of the new method. The results indicate that there is a significant difference between the frequency response of healthy and effused lungs, which suggests that the new technique may be suitable for the clinical diagnosis of pleural effusion.

Segmentation and computer assisted design tools have the potential to test the validity of simulated surgical procedures, e.g., trochleoplasty. A repeatable measurement method for three dimensional femur models that enables quantification of knee parameters of the distal femur is presented. Fifteen healthy knees are analysed using the method to provide a training set for an artificial neural network. The aim is to use this artificial neural network for the prediction of parameter values that describe the shape of a normal trochlear groove geometry. This is achieved by feeding the artificial neural network with the unaffected parameters of a dysplastic knee. Four dysplastic knees (Type A through D) are virtually redesigned by way of morphing the groove geometries based on the suggested shape from the artificial neural network. Each of the four resulting shapes is analysed and compared to its initial dysplastic shape in terms of three anteroposterior dimensions: lateral, central and medial. For the four knees the trochlear depth is increased, the ventral trochlear prominence reduced and the sulcus angle corrected to within published normal ranges. The results show a lateral facet elevation inadequate, with a sulcus deepening or a depression trochleoplasty more beneficial to correct trochlear dysplasia.

Patients in critical care with lung injuries require oxygenation, but current methods are not applicable for all situations. The most common method, Extracorporeal Membrane Oxygenation is an expensive procedure and requires highly trained staff. Respiratory Assist Catheters (RACs) could be used as an alternative because they do not place extra stress on the lungs, are easy to implement, cost-effective and are available for immediate use in clinical settings or in first aid situations. This paper describes experiments and simulations to evaluate the feasibility of intravenously oxygenating the blood using microbubbles. The tests included in vivo and ex vivo tests using animal models to investigate both the dissolution times of the microbubbles as well as the physiological effects of an intravenously placed device. Numerical simulations based on the dissolution rate of oxygen in venous blood were also completed. The results indicate that the dissolution times for the micro bubbles are too slow for the device to be successful in clinical practice.

Ventilation during neonatal cardiopulmonary resuscitation (NCPR) may adversely affect chest compression (CC) quality (i.e., the delivery of consistent and sufficiently deep CC) since current guidelines recommend a 3:1 CC to ventilation ratio which is much higher than the 30:2 CC to ventilation ratio recommended for children and adults. In this study the influence of ventilation on CC performance during NCPR was investigated by measuring the CC depth and force during simulated unventilated and ventilated NCPR using an infant training manikin. The results obtained indicate that ventilation may exert a significant influence on CC performance during NCPR due to dynamic changes in chest properties (i.e., stiffness and damping) which likely occur due to the high frequency of inflation and deflation of the manikin lungs during NCPR at the 3:1 CC to ventilation ratio recommended by the guidelines.