Digital messaging to support control for type 2 diabetes (StAR2D): a multicentre randomised controlled trial.

BACKGROUND: Failure to take medicines for diabetes as prescribed contributes to poor outcomes from the condition. Mobile phones are ubiquitous and short message service (SMS) texts have shown promise as a low-cost intervention. We tested the effectiveness of SMS-text messaging in improving outcomes in adults with type 2 diabetes. METHODS: StAR2D was a 12-month two-arm randomised trial of SMS-text messaging and usual care in Cape Town, South Africa and Lilongwe, Malawi. Messages used behaviour change theory and were developed with patients and staff. The intervention group received four messages each week. The primary outcome was change in HbA1c. Secondary outcomes were the proportion of patients who collected > 80% medication and changes in systolic blood pressure, lipids, cardiovascular risk, and the proportion of the participants reaching treatment goals. RESULTS: The trial took place between 1 October, 2016 and 1 October 2018, 1186 participants were randomised to intervention (593) and control (593) groups. 91% of participants completed follow-up. There was a reduction in HbA1c (DCCT) in both groups but not in mean change (95% CI) between groups (- 0.08% (- 0.31 to 0.16) (IFCC - 0.82 mmol/mol (- 3.44 to 1.79). There was a small but not significant increase in the proportions of participants likely to have collected 80% or more of medication (Relative risk 1.11 (0.84 to 1.47; P = 0.47). There was a significant difference between groups in change in systolic blood pressure from baseline of 3.46 mmHg (1.48 to 5.44, P = 0.001) in favour of the intervention group. The between group difference in change in 10-year risk of coronary heart disease was - 0.71% (- 1.46 to 0.04, P = 0.064). The proportion of participants meeting treatment goals in the intervention group was 36.0% and in the control group 26.8% (Relative risk 1.36 (1.13 to 1.63, P = 0.001). Participants reported many challenges to adherence despite finding messages acceptable and useful. CONCLUSIONS: Whilst SMS text messages do not lead to improved glycaemia in these low-resource settings there appeared to be an impact on blood pressure and achievement of treatment goals but the mechanisms for this are unclear. Text messages alone, may be unsuccessful unless accompanied by health system strengthening and other forms of self-management support for type 2 diabetes. TRIAL REGISTRATION: Trial registration: ISRCTN, ISRCTN70768808. Registered 1 July 2015, http://www.isrctn.com/I ISRCTN70768808.

Contactless skin perfusion monitoring with video cameras: tracking pharmacological vasoconstriction and vasodilation using photoplethysmographic changes.

Objectives.Clinical assessment of skin perfusion informs prognosis in critically ill patients. Video camera monitoring could provide an objective, continuous method to monitor skin perfusion. In this prospective, interventional study of healthy volunteers, we tested whether video camera-derived photoplethysmography imaging and colour measurements could detect drug-induced skin perfusion changes.Approach.We monitored the lower limbs of 30 volunteers using video cameras while administering phenylephrine (a vasoconstrictor) and glyceryl trinitrate (a vasodilator). We report relative pixel intensity changes from baseline, as absolute values are sensitive to environmental factors. The primary outcome was the pre- to peak- infusion green channel amplitude change in the pulsatile PPGi waveform component. Secondary outcomes were pre-to-peak changes in the photoplethysmographic imaging waveform baseline, skin colour hue and skin colour saturation.Main results.The 30 participants had a median age of 29 years (IQR 25-34), sixteen (53%) were male. A 34.7% (p= 0.0001) mean decrease in the amplitude of the pulsatile photoplethysmographic imaging waveform occurred following phenylephrine infusion. A 30.7% (p= 0.000004) mean increase occurred following glyceryl trinitrate infusion. The photoplethysmographic imaging baseline decreased with phenylephrine by 2.1% (p= 0.000 02) and increased with glyceryl trinitrate by 0.5% (p= 0.026). Skin colour hue changed in opposite direction with phenylephrine (-0.0013,p= 0.0002) and glyceryl trinitrate (+0.0006,p= 0.019). Skin colour saturation decreased with phenylephrine by 0.0022 (p= 0.0002), with no significant change observed with glyceryl trinitrate (+0.0005,p= 0.21).Significance.Drug-induced vasoconstriction and vasodilation are associated with detectable changes in photoplethysmographic imaging waveform parameters and skin hue. Our findings suggest video cameras have great potential for continuous, contactless skin perfusion monitoring.

Automated method for detecting and reading seven-segment digits from images of blood glucose metres and blood pressure monitors.

There is an increasing need for fast and accurate transfer of readings from blood glucose metres and blood pressure monitors to a smartphone mHealth application, without a dependency on Bluetooth technology. Most of the medical devices recommended for home monitoring use a seven-segment display to show the recorded measurement to the patient. We aimed to achieve accurate detection and reading of the seven-segment digits displayed on these medical devices using an image taken in a realistic scenario by a smartphone camera. A synthetic dataset of seven-segment digits was developed in order to train and test a digit classifier. A dataset containing realistic images of blood glucose metres and blood pressure monitors using a variety of smartphone cameras was also created. The digit classifier was evaluated on a dataset of seven-segment digits manually extracted from the medical device images. These datasets along with the code for its development have been made public. The developed algorithm first preprocessed the input image using retinex with two bilateral filters and adaptive histogram equalisation. Subsequently, the digit segments were automatically located within the image by two techniques operating in parallel: Maximally Stable Extremal Regions (MSER) and connected components of a binarised image. A filtering and clustering algorithm was then designed to combine digit segments to form seven-segment digits. The resulting digits were classified using a Histogram of Orientated Gradients (HOG) feature set and a neural network trained on the synthetic digits. The model achieved 93% accuracy on digits found on the medical devices. The digit location algorithm achieved a F1 score of 0.87 and 0.80 on images of blood glucose metres and blood pressure monitors respectively. Very few assumptions were made of the locations of the digits on the devices so that the proposed algorithm can be easily implemented on new devices.

Application of mobile phone technology for managing chemotherapy-associated side-effects.

BACKGROUND: Novel mobile phone technology linked to a server that communicates patients' symptoms to healthcare professionals has been adapted to register the side- effects of chemotherapy and provide advice on management of toxicity. We report a feasibility study to examine the utility of home monitoring of patients' symptoms via a mobile phone. METHODS: Six colon cancer patients receiving adjuvant chemotherapy, entered symptom data onto user friendly screens on a mobile phone twice daily. This 'real time' self assessment of nausea, vomiting, mucositis, diarrhoea and hand-foot syndrome and measurement of temperature was sent via a secured connection to a remote computer. In the event of moderate or severe symptoms (generating amber and red alerts respectively), the nurse was immediately alerted by the computer, via a pager. The nurse then contacted the patient to reinforce the automatic advice sent to the patient on their phone and to assess the patient using clinical algorithms. RESULTS: The patient used the mobile phones during the first two cycles of chemotherapy. The data were successfully analysed by the server software and alerts were generated alerting the study nurses to patients' symptoms at the appropriate time. There were 91 alerts-54 red and 37 amber; 54% (29/54) of the red alerts were data delay and transmission problems which were swiftly rectified. The remaining red alerts were managed appropriately by the study nurses. Both patients and staff felt confident in this approach to symptom management. CONCLUSIONS: This study demonstrates that the technology for monitoring patients' symptoms worked well. The patients felt secure in the knowledge that their symptoms were being closely monitored and that they were participating effectively in their own care management.

Synchronization between arterial blood pressure and cerebral oxyhaemoglobin concentration investigated by wavelet cross-correlation.

Wavelet cross-correlation (WCC) is used to analyse the relationship between low-frequency oscillations in near-infrared spectroscopy (NIRS) measured cerebral oxyhaemoglobin (O(2)Hb) and mean arterial blood pressure (MAP) in patients suffering from autonomic failure and age-matched controls. Statistically significant differences are found in the wavelet scale of maximum cross-correlation upon posture change in patients, but not in controls. We propose that WCC analysis of the relationship between O(2)Hb and MAP provides a useful method of investigating the dynamics of cerebral autoregulation using the spontaneous low-frequency oscillations that are typically observed in both variables without having to make the assumption of stationarity of the time series. It is suggested that for a short-duration clinical test previous transfer-function-based approaches to analyse this relationship may suffer due to the inherent nonstationarity of low-frequency oscillations that are observed in the resting brain.

Mobile phone technology in the management of asthma.

Peak flow monitoring is widely recommended as part of a self-management plan for asthma. We conducted an observational study using electronic peak flow monitoring and mobile phone technology in a UK general practice population over a nine-month period. Patients between 12 and 55 years of age who required treatment with regular inhaled steroids and (as needed) bronchodilators were recruited from nine general practices. Patients were included if their asthma was considered stable (i.e. no exacerbation in the previous three months). No therapeutic intervention was proposed. The primary outcome measure was compliance. In all, 69% of the 46 participants who filled in the post-study questionnaire were 'satisfied' or 'very satisfied' by the study, citing the ease of use and the increased autonomy and understanding of asthma as the main advantages. In total, 74% indicated that the system had helped to improve their ability to manage their symptoms. The most positive features of the telemedicine system were described as follows: increased awareness and information about asthma, improved ability to monitor/manage the condition with the feedback screens on the mobile phone and ease of use.

Quantitative analysis of immunological reactions on silicon surfaces by multiple-angle Brewster angle reflectometry.

An optical biosensing instrument has been developed for the quantitative analysis of immunological reactions on biochemically sensitized surfaces. It is based on the measurement of reflectance changes of polarized laser light incident on high refractive index substrates at angles close to the pseudo-Brewster angle. Multiple-angle Brewster angle reflectometry (MABAR) has been used to investigate the binding of anti-human serum albumin (a-HSA) to human serum albumin (HSA) coated silicon surfaces. The concentration dependence and reaction kinetics of antibody-antigen complex formation have been studied using red and green He-Ne laser light. A significant increase in sensitivity has been observed with green light.

Reflectance pulse oximetry measurements from the retinal fundus.

Conventional transmission pulse oximetry is a noninvasive technique for the continuous monitoring of arterial oxygen saturation (SaO2) from peripheral vascular beds such as the finger tip or earlobe. In this paper we propose to exploit the unique transparency of the ocular media to make reflectance pulse oximetry measurements on the retinal fundus. This technique potentially offers significant advantages over conventional pulse oximetry, primarily the ability to monitor cerebral, as opposed to peripheral, oxygen saturation. We have developed an in vitro system to stimulate the retinal circulation and ocular optics. This system consists of a flexible cuvette located in a model eye and an extracorporeal blood circuit to stimulate arterial blood flow. The system was used to investigate the relationship between SaO2 and the R/IR ratio in reflectance pulse oximetry. To enable in vivo measurements to be made, we also modified a standard haptic contact lens to hold the pulse oximeter probe in front of the pupil. In a preliminary study, the lens was fitted to an awake volunteer and cardiac-synchronous signals were detected by the retinal pulse oximeter.

An optical method for the determination of platelet count in platelet samples contaminated with red blood cells.

We present a simple photometric method to determine the total concentration of platelets present in a sample independently of red blood cell concentration. Standard optical density curves for platelet samples ranging in concentration from 0 to 1.5 x 10(9) cells/ml and contaminated with red blood cells ranging in concentration from 0 to 0.03 x 10(9) cells/ml are determined. A study of the absorbance spectra of red blood cells and platelets suggests that by calculating the absorbance difference between two wavelengths, an estimate of red blood cell concentration can be made. Then, in the second step of this two-step method, the individual absorbance measurements at the two wavelengths are matched to the standard values determined previously to derive an estimate of platelet concentration. In a trial of 62 unknown platelet samples contaminated with red blood cells, the standard deviation for the error in platelet count was 0.16 x 10(9) cells/ml with a mean difference of 0.011 x 10(9) platelets/ml. We conclude that our method may be useful in laboratories not equipped with electronic cell counters as well as in applications such as the development of noninvasive measurements of platelet concentration in platelet transfusion packs.

Analysis of dynamic MR breast images using a model of contrast enhancement.

We describe a model of dynamic contrast enhancement in breast MRI designed to aid the radiologist in cases for which X-ray mammography is ineffective. The breasts are segmented from the image slices by a dynamic programming algorithm after morphological opening. A pharmacokinetic model has been derived to fit the rise in intensities after injection of a contrast agent, in a way that facilitates investigation of the effects of different models of bolus injection. The pharmacokinetic model is used in a modified Horn-Schunck algorithm to correct for motion effects during the seven minute acquisition period. The results show significant localization of tumours and enable discrimination of cancerous tissue. In particular, we illustrate the approach with an image that shows a carcinoma, whose appearance and localization are greatly improved by the registration algorithm.

Sleep studies of adults with severe or profound mental retardation and epilepsy.

Sleep patterns of people with mental retardation have received little research attention. This is an important gap in knowledge because understanding the relation between sleep and wakefulness may be critical to care provision. Descriptive sleep information on 28 people with severe or profound mental retardation and epilepsy was presented here. Sleep EEG data, studied both conventionally and by means of a neural network-based sleep analysis system suggest atypical sleep stages with significant depletion of REM sleep and a predominance of "indiscriminate" non-REM sleep. Sleep diaries completed by caregivers reveal lengthy sleep period times, especially among those with profound mental retardation. Possible explanations for these results and their implications were discussed.

Estimations of error bounds for neural-network function approximators.

Neural networks are being increasingly used for problems involving function approximation. However, a key limitation of neural methods is the lack of a measure of how much confidence can be placed in output estimates. In the last few years many authors have addressed this shortcoming from various angles, focusing primarily on predicting output bounds as a function of the trained network's characteristics, typically as defined by the Hessian matrix. In this paper the problem of the effect of errors or noise in the presented, input, vector is examined and a method based on perturbation analysis of determining output bounds based on both the error in the input vector and the imperfections in the weight values after training is presented and demonstrated.

Pulse-stream VLSI neural networks mixing analog and digital techniques.

The pulse-stream technique, which represents neural states as sequences of pulses, is reviewed. Several general issues are raised, and generic methods appraised, for pulsed encoding, arithmetic, and intercommunication schemes. Two contrasting synapse designs are presented and compared. The first is based on a fully analog computational form in which the only digital component is the signaling mechanism itself-asynchronous, pulse-rate encoded digital voltage pulses. In this circuit, multiplication occurs in the voltage/current domain. The second design uses more conventional digital memory for weight storage, with synapse circuits based on pulse stretching. Integrated circuits implementing up to 15000 analog, fully programmable synaptic connections are described. A demonstrator project is described in which a small robot localization network is implemented using asynchronous, analog, pulse-stream devices.

Integrated pulse stream neural networks: results, issues, and pointers.

Results from working analog VLSI implementations of two different pulse stream neural network forms are reported. The circuits are rendered relatively invariant to processing variations, and the problem of cascadability of synapses to form large systems is addressed. A strategy for interchip communication of large numbers of neural states has been implemented in silicon and results are presented. The circuits demonstrated confront many of the issues that blight massively parallel analog systems, and offer solutions.

Segmenting cardiac-related data using sleep stages increases separation between normal subjects and apnoeic patients.

Inter-patient comparisons of cardiovascular metrics indicative of patient health have been shown to be successful in differentiating patients on a group rather than an individual level. This is in part due to the range of mental (as well as physical) activity-based variations for each patient and the difficulty assessing physical and mental activity during conscious states. In order to provide an objective scale for measuring central nervous system activity during sleep, the heart rate (RR) interval time series is divided into coarse sleep stage segments in which the LF/HF-ratio (the relative balance between low and high frequency power) is estimated for age and sex-matched populations of apnoeic and healthy subjects. Activity-based noise is therefore reduced and a more useful comparison of heart rate variability can be made. Additionally, the spectral estimation performances of the FFT and the Lomb-Scargle periodogram (LSP), a Fourier-based technique for unevenly sampled time series are compared. Separation of patients according to condition is shown to be more pronounced when using the LSP than the FFT. Furthermore, separation is found to be most marked in slow wave sleep.

New method of automated sleep quantification.

Since its discovery some 50 years ago, the electro-encephalogram (EEG) has formed the basis for classification of sleep into several stages, either laboriously performed by visual examination of the EEG and related signals or, more recently, by automated techniques. Both visual scoring and most automated analyses are highly subjective and rely on application of a predefined set of rules. A method of analysing the EEG which requires no such application of rules and aims to give some indication of the dynamics of sleep in humans is proposed in the paper.

Pulse oximetry: theoretical and experimental models.

In the paper a pulse oximetry model is developed using an approach which combines both theoretical and empirical modelling. The optical properties of whole blood are measured as a function of cuvette depth by transmission spectrophotometry using red (660 nm) and infra-red (950 nm) light-emitting diodes as light sources. Twersky's theoretical model gives the best fit to the experimental data. A simple theoretical model which takes into account the nonlinear relationship between optical density and cuvette depth is then used to obtain an expression for the R:IR ratio, which relates the measurement of transmission at the two wavelengths. The R:IR ratio is found to be more or less independent of cuvette depth (SD = 0.14 at 100 per cent SaO2). To validate the predictions of the theoretical model, the results of a previous experiment in which the relationship between SaO2 and the R:IR ratio was recorded using a flexible cuvette are used. The experimental values are found to lie within one standard deviation from the theoretical curve relating SaO2 and the R:IR ratio. It is argued that a reasonably accurate model for pulse oximetry which is based on whole blood and not haemoglobin solutions has been developed.

Linear and non-linear methods for automatic seizure detection in scalp electro-encephalogram recordings.

The electro-encephalogram is a time-varying signal that measures electrical activity in the brain. A conceptually intuitive non-linear technique, multi-dimensional probability evolution (MDPE), is introduced. It is based on the time evolution of the probability density function within a multi-dimensional state space. A synthetic recording is employed to illustrate why MDPE is capable of detecting changes in the underlying dynamics that are invisible to linear statistics. If a non-linear statistic cannot outperform a simple linear statistic such as variance, then there is no reason to advocate its use. Both variance and MDPE were able to detect the seizure in each of the ten scalp EEG recordings investigated. Although MDPE produced fewer false positives, there is no firm evidence to suggest that MDPE, or any other non-linear statistic considered, outperforms variance-based methods at identifying seizures.