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.

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.

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.

Non-contact video-based vital sign monitoring using ambient light and auto-regressive models.

Remote sensing of the reflectance photoplethysmogram using a video camera typically positioned 1 m away from the patient's face is a promising method for monitoring the vital signs of patients without attaching any electrodes or sensors to them. Most of the papers in the literature on non-contact vital sign monitoring report results on human volunteers in controlled environments. We have been able to obtain estimates of heart rate and respiratory rate and preliminary results on changes in oxygen saturation from double-monitored patients undergoing haemodialysis in the Oxford Kidney Unit. To achieve this, we have devised a novel method of cancelling out aliased frequency components caused by artificial light flicker, using auto-regressive (AR) modelling and pole cancellation. Secondly, we have been able to construct accurate maps of the spatial distribution of heart rate and respiratory rate information from the coefficients of the AR model. In stable sections with minimal patient motion, the mean absolute error between the camera-derived estimate of heart rate and the reference value from a pulse oximeter is similar to the mean absolute error between two pulse oximeter measurements at different sites (finger and earlobe). The activities of daily living affect the respiratory rate, but the camera-derived estimates of this parameter are at least as accurate as those derived from a thoracic expansion sensor (chest belt). During a period of obstructive sleep apnoea, we tracked changes in oxygen saturation using the ratio of normalized reflectance changes in two colour channels (red and blue), but this required calibration against the reference data from a pulse oximeter.

A two-class approach to the detection of physiological deterioration in patient vital signs, with clinical label refinement.

Hospital patient outcomes can be improved by the early identification of physiological deterioration. Automatic methods of detecting patient deterioration in vital-sign data typically attempt to identify deviations from assumed normal physiological conditions, which is a one-class approach to classification. This paper investigates the use of a two-class approach, in which abnormal physiology is modelled explicitly. The success of such a method relies on the accuracy of data labels provided by clinical experts, which may be incomplete (due to large dataset size) or imprecise (due to clinical labels covering intervals, rather than each data point within those intervals). We propose a novel method of refining clinical labels such that the two-class classification approach may be adopted for identifying patient deterioration. We demonstrate the effectiveness of the proposed methods using a large dataset acquired in a 24-bed hospital step-down unit.

Photoplethysmographic derivation of respiratory rate: a review of relevant physiology.

An abnormal respiratory rate is often the earliest sign of critical illness. A reliable estimate of respiratory rate is vital in the application of remote telemonitoring systems, which may facilitate early supported discharge from hospital or prompt recognition of physiological deterioration in high-risk patient groups. Traditional approaches use analysis of respiratory sinus arrhythmia from the electrocardiogram (ECG), but this phenomenon is predominantly limited to the young and healthy. Analysis of the photoplethysmogram (PPG) waveform offers an alternative means of non-invasive respiratory rate monitoring, but further development is required to enable reliable estimates. This review conceptualizes the challenge by discussing the effect of respiration on the PPG waveform and the key physiological mechanisms that underpin the derivation of respiratory rate from the PPG.

Determining which automatic digital blood pressure device performs adequately: a systematic review.

The aim of this study is to systematically examine the proportion of accurate readings attained by automatic digital blood pressure (BP) devices in published validation studies. We included studies of automatic digital BP devices using recognized protocols. We summarized the data as mean and s.d. of differences between measured and observed BP, and proportion of measurements within 5 mm Hg. We included 79 articles (10,783 participants) reporting 113 studies from 22 different countries. Overall, 25/31 (81%), 37/41 (90%) and 34/35 (97%) devices passed the relevant protocols [BHS, AAMI and ESH international protocol (ESH-IP), respectively]. For devices that passed the BHS protocol, the proportion of measured values within 5 mm Hg of the observed value ranged from 60 to 86% (AAMI protocol 47-94% and ESH-IP 54-89%). The results for the same device varied significantly when a different protocol was used (Omron HEM-907 80% of readings were within 5 mm Hg using the AAMI protocol compared with 62% with the ESH-IP). Even devices with a mean difference of zero show high variation: a device with 74% of BP measurements within 5 mm Hg would require six further BP measurements to reduce variation to 95% of readings within 5 mm Hg. Current protocols for validating BP monitors give no guarantee of accuracy in clinical practice. Devices may pass even the most rigorous protocol with as few as 60% of readings within 5 mm Hg of the observed value. Multiple readings are essential to provide clinicians and patients with accurate information on which to base diagnostic and treatment decisions.

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.

A randomised controlled trial of the effect of continuous electronic physiological monitoring on the adverse event rate in high risk medical and surgical patients.

We conducted a randomised controlled trial of mandated five-channel physiological monitoring vs standard care, in acute medical and surgical wards in a single UK teaching hospital. In all, 402 high-risk medical and surgical patients were studied. The primary outcome was the proportion of patients experiencing one or more major adverse events, including urgent staff calls, changes to higher care levels, cardiac arrests or death, in 96 h following randomisation. Secondary outcomes were the proportion of patients requiring acute treatment changes, and the 30-day and hospital mortality. In the 96 h following randomisation, 113 (56%) patients in the monitored arm and 116 (58%) in the control arm (OR 0.94, 95% CI 0.63-1.40, p = 0.76) had a major event. An acute change in treatment was necessary in 107 (53%) monitored patients and 101 (50%) control patients (OR 0.55, 95% CI 0.87-1.29). Thirty-four (17%) monitored patients and 35 (17%) control patients died within 30 days. Thirteen patients in the control group received full five-channel monitoring at the request of the ward staff. We conclude that mandated electronic vital signs monitoring in high risk medical and surgical patients has no effect on adverse events or mortality.

Combined transfer function analysis and modelling of cerebral autoregulation.

The clinical importance of cerebral autoregulation has resulted in a significant body of literature that attempts both to model the underlying physiological processes and to estimate the mathematical relationships between clinically measurable variables, the most common of which are Arterial Blood Pressure and Cerebral Blood Flow Velocity. These approaches have, however, rarely been used together to interpret clinical data. A simple model of cerebral autoregulation is thus proposed here, based on a flow dependent feedback mechanism with gain and time constant that adjusts arterial compliance. Analysis of this model shows that it closely approximates a second order system for typical values of physiological parameters. The model parameters can be optimally estimated from available experimental data for the Impulse Response (IR), yielding physiologically reasonable values, although there is one free parameter that must be fixed. The effects of changes in feedback gain and time constant are found to be significant on the predicted IR and can thus be estimated robustly from experimental data. The effects of elevated baseline Intracranial Pressure (ICP) are found to be exactly equivalent to a reduced feedback gain, although the solution is much less sensitive to the former effect. A transfer function approach can be used to estimate autoregulation status clinically using a physiologically-based model, thus providing greater insight into the processes that govern cerebral autoregulation.

Integrated monitoring and analysis for early warning of patient deterioration.

Recently there has been an upsurge of interest in strategies for detecting at-risk patients in order to trigger the timely intervention of a Medical Emergency Team (MET), also known as a Rapid Response Team (RRT). We review a real-time automated system, BioSign, which tracks patient status by combining information from vital signs monitored non-invasively on the general ward. BioSign fuses the vital signs in order to produce a single-parameter representation of patient status, the Patient Status Index. The data fusion method adopted in BioSign is a probabilistic model of normality in five dimensions, previously learnt from the vital sign data acquired from a representative sample of patients. BioSign alerts occur either when a single vital sign deviates by close to +/-3 standard deviations from its normal value or when two or more vital signs depart from normality, but by a smaller amount. In a trial with high-risk elective/emergency surgery or medical patients, BioSign alerts were generated, on average, every 8 hours; 95% of these were classified as 'True' by clinical experts. Retrospective analysis has also shown that the data fusion algorithm in BioSign is capable of detecting critical events in advance of single-channel alerts.

A systematic review of telemedicine interventions to support blood glucose self-monitoring in diabetes.

AIMS: To evaluate evidence for feasibility, acceptability and cost-effectiveness of diabetes telemedicine applications. METHODS: MEDLINE, EMBASE, PSYCHINFO, CINAHL, Cochrane, and INSPEC were searched using the terms diabetes and telemedicine for clinical studies using electronic transfer of blood glucose results in people with diabetes. The technology used, trial design and clinical outcome measures used were extracted for trials and prospective cohort studies. Randomized controlled trials with HbA(1c) as an outcome were pooled using standard meta-analytical methods. RESULTS: We identified 539 papers among which 32 papers described 10 prospective cohort studies, 12 parallel group randomized controlled trials (RCT), three crossover trials, and one non-parallel group trial. Only two studies described full details of randomization, blinding of outcomes and dropouts and withdrawals. Electronic transfer of glucose results appears feasible in a clinical setting. Only two of the RCTs included more than 100 patients, and only three extended to 1 year. Only one study was designed to show that telemedicine interventions might replace clinic interventions without deterioration in HbA(1c). Results pooled from the nine RCTs with reported data did not provide evidence that the interventions were effective in reducing HbA(1c) (-0.1%, 95% CI -0.4% to 0.04%). CONCLUSIONS: Telemedicine solutions for diabetes care are feasible and acceptable, but evidence for their effectiveness in improving HbA(1c) or reducing costs while maintaining HbA(1c) levels, or improving other aspects of diabetes management is not strong. Further research should seek to understand how telemedicine might enhance educational and self-management interventions and RCTs are required to examine cost-effectiveness.

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.

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.

Time-frequency analysis of the ECG in the diagnosis of vasovagal syndrome in older people.

The Smoothed Pseudo Wigner-Ville Distribution (SPWVD) is used for the time-frequency analysis of variations in RR interval. A novel technique to determine the smoothing window lengths is implemented, and a new heart rate variability (HRV) metric is developed, instantaneous center frequency variability (ICFV), which uses the time-frequency map generated by the SPWVD. The technique is then applied to 50 patients with unexplained falls and age > 60, undergoing head-upright tilt table testing (HUT). Eighteen of the patients were diagnosed with vasovagal syndrome. Attempts at syncope prediction using the new metric is an improvement on traditional techniques: an ICFV less than 0.07 Hz from 90 s to 180 s after tilt is predictive of a negative test (negative predictive value: 0.77). The comorbidity and autonomic degeneration present in elderly patients are thought to be responsible for lowering the negative predictive value.

Efficient callus formation and plant regeneration of goosegrass [Eleusine indica (L.) Gaertn.].

Efficient methods in totipotent callus formation, cell suspension culture establishment and whole-plant regeneration have been developed for the goosegrass [ Eleusine indica (L.) Gaertn.] and its dinitroaniline-resistant biotypes. The optimum medium for inducing morphogenic calli consisted of N6 basal salts and B5 vitamins supplemented with 1-2 mg l(-1) 2,4-dichlorophenoxyacetic acid (2,4-D), 2 mg l(-1) glycine, 100 mg l(-1) asparagine, 100 mg l(-1) casein hydrolysate, 30 g l(-1) sucrose and 0.6% agar, pH 5.7. The presence of organogenic and embryogenic structures in these calli was histologically documented. Cell suspension cultures derived from young calli were established in a liquid medium with the same composition. Morphogenic structures of direct shoots and somatic embryos were grown into rooted plantlets on medium containing MS basal salts, B5 vitamins, 1 mg l(-1) kinetin (Kn) and 0.1 mg l(-1) indole-3-acetic acid (IAA), 3% sucrose, 0.6% agar, pH 5.7. Calli derived from the R-biotype of E. indica possessed a high resistance to trifluralin (dinitroaniline herbicide) and cross-resistance to a structurally non-related herbicide, amiprophosmethyl (phosphorothioamidate herbicide), as did the original resistant plants. Embryogenic cell suspension culture was a better source of E. indica protoplasts than callus or mesophyll tissue. The enzyme solution containing 1.5% cellulase Onozuka R-10, 0.5% driselase, 1% pectolyase Y-23, 0.5% hemicellulase and N(6) mineral salts with an additional 0.2 M KCl and 0.1 M CaCl(2) (pH 5.4-5.5) was used for protoplast isolation. The purified protoplasts were cultivated in KM8p liquid medium supplemented with 2 mg l(-1) 2,4-D and 0.2 mg l(-1) Kn.

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.