Cross-Modal Health State Estimation

Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geospatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.Comment: Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18/1

Maximal Exercise Capacity in Chronic Kidney Disease Stage 4-5 Patients Transitioning to Renal Replacement Therapy or Continuing Conservative Care: A Longitudinal Follow-Up Study

Introduction: Chronic kidney disease (CKD) is associated with impaired maximal exercise capacity (MEC). However, data are scarce on the development of MEC in CKD stage 4-5 patients transitioning to renal replacement therapy (RRT).Methods: We explored the change in MEC measured in watts (Wlast4) with 2 consecutive maximal bicycle stress ergometry tests in 122 CKD stage 4-5 patients transitioning to dialysis and transplantation in an observational follow-up study.Results: Mean age was 58.9 ± 13.9 years and 43 (35.2%) were female. Mean time between the baseline and follow-up ergometry tests was 1,012 ± 327 days and 29 (23.8%) patients had not initiated RRT, 50 (41.0%) were undergoing dialysis, and 43 (35.2%) had received a kidney transplant at the time of the follow-up ergometry test. The mean Wlast4 was 91 ± 37 W and 84 ± 37 W for the baseline and follow-up ergometry tests, respectively (p Conclusion: MEC declined or remained poor in advanced CKD patients transitioning to RRT or continuing conservative care in this observational study. Mean capillary blood bicarbonate was independently associated with the development of MEC.</p

Interatrial block, P terminal force or fragmented QRS do not predict new-onset atrial fibrillation in patients with severe chronic kidney disease

Background: The prevalence of left atrial enlargement (LAE) and fragmented QRS (fQRS) diagnosed using ECG criteria in patients with severe chronic kidney disease (CKD) is unknown. Furthermore, there is limited data on predicting new-onset atrial fibrillation (AF) with LAE or fQRS in this patient group. Methods: We enrolled 165 consecutive non-dialysis patients with CKD stage 4-5 without prior AF diagnosis between 2013 and 2017 in a prospective follow-up cohort study. LAE was defined as total P-wave duration >= 120ms in lead II >1 biphasic P-waves in leads II, III or aVF; or duration of terminal negative portion of P-wave >40ms or depth of terminal negative portion of P-wave >1mm in lead V-1 from a baseline ECG, respectively. fQRS was defined as the presence of a notched R or S wave or the presence of >= 1 additional R waves (R') or; in the presence of a wide QRS complex (>120ms), >2 notches in R or S waves in two contiguous leads corresponding to a myocardial region, respectively. Results: Mean age of the patients was 59 (SD 14) years, 56/165 (33.9%) were female and the mean estimated glomerular filtration rate was 12.8ml/min/1.73m(2). Altogether 29/165 (17.6%) patients were observed with new-onset AF within median follow-up of 3 [IQR 3, range 2-6] years. At baseline, 137/165 (83.0%) and 144/165 (87.3%) patients were observed with LAE and fQRS, respectively. Furthermore, LAE and fQRS co-existed in 121/165 (73.3%) patients. Neither findings were associated with the risk of new-onset AF within follow-up. Conclusion: The prevalence of LAE and fQRS at baseline in this study on CKD stage 4-5 patients not on dialysis was very high. However, LAE or fQRS failed to predict occurrence of new-onset AF in these patients

Reversibility of myocardial metabolism and remodelling in morbidly obese patients 6 months after bariatric surgery

AbstractAIMS: To study myocardial substrate uptake, structure and function, before and after bariatric surgery, to clarify the interaction between myocardial metabolism and cardiac remodelling in morbid obesity.METHODS: We studied 46 obese patients (age 44 ± 10 years, body mass index [BMI] 42 ± 4 kg/m2 ), including 18 with type 2 diabetes (T2D) before and 6 months after bariatric surgery and 25 healthy age-matched control group subjects. Myocardial fasting free fatty acid uptake (MFAU) and insulin-stimulated myocardial glucose uptake (MGU) were measured using positron-emission tomography. Myocardial structure and function, and myocardial triglyceride content (MTGC) and intrathoracic fat were measured using magnetic resonance imaging and magnetic resonance spectroscopy.RESULTS: The morbidly obese study participants, with or without T2D, had cardiac hypertrophy, impaired myocardial function and substrate metabolism compared with the control group. Surgery led to marked weight reduction and remission of T2D in most of the participants. Postoperatively, myocardial function and structure improved and myocardial substrate metabolism normalized. Intrathoracic fat, but not MTGC, was reduced. Before surgery, BMI and MFAU correlated with left ventricular hypertrophy, and BMI, age and intrathoracic fat mass were the main variables associated with cardiac function. The improvement in whole-body insulin sensitivity correlated positively with the increase in MGU and the decrease in MFAU.CONCLUSIONS: In the present study, obesity and age, rather than myocardial substrate uptake, were the causes of cardiac remodelling in morbidly obese patients with or without T2D. Cardiac remodelling and impaired myocardial substrate metabolism are reversible after surgically induced weight loss and amelioration of T2D.</div

Effects of cognac on coronary flow reserve and plasma antioxidant status in healthy young men

<p>Abstract</p> <p>Background</p> <p>The cardioprotective effects of certain alcoholic beverages are partly related to their polyphenol content, which may improve the vasodilatory reactivity of arteries. Effect of cognac on coronary circulation, however, remains unknown. The purpose of this randomized controlled cross-over study was to determine whether moderate doses of cognac improve coronary reactivity as assessed with cold pressor testing (CPT) and coronary flow reserve (CFR) measument.</p> <p>Methods</p> <p>Study group consisted of 23 subjects. Coronary flow velocity and epicardial diameter was assessed using transthoracic echocardiography at rest, during CPT and adenosine infusion-derived CFR measurements before drinking, after a moderate (1.2 ± 0.1 dl) and an escalating high dose (total amount 2.4 ± 0.3 dl) of cognac. To explore the bioavailability of antioxidants, the antioxidant contents of cognac was measured and the absorption from the digestive tract was verified by plasma antioxidant capacity determination.</p> <p>Results</p> <p>Serum alcohol levels increased to 1.2 ± 0.2‰ and plasma antioxidant capacity from 301 ± 43.9 μmol/l to 320 ± 25.0 μmol/l by 7.6 ± 11.8%, (p = 0.01) after high doses of cognac. There was no significant change in flow velocity during CPT after cognac ingestion compared to control day. CFR was 4.4 ± 0.8, 4.1 ± 0.9 (p = NS), and 4.5 ± 1.2 (p = NS) before drinking and after moderate and high doses on cognac day, and 4.5 ± 1.4, and 4.0 ± 1.2 (p = NS) on control day.</p> <p>Conclusion</p> <p>Cognac increased plasma antioxidant capacity, but it had no effect on coronary circulation in healthy young men.</p> <p>Trial Registration</p> <p>NCT00330213</p

Application of data fusion techniques and technologies for wearable health monitoring

Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market

Reaaliaikainen visuaalinen odometria

Visuaalisella odometrialla estimoidaan ajoneuvon, ihmisen tai robotin liikettä käyttäen syötteenä kuvaa yhdestä tai useammasta kamerasta. Sovelluskohteita on robotiikassa, autoteollisuudessa, asustemikroissa ja lisätyssä todellisuudessa. Se on hyvä lisä navigointijärjestelmiin, koska se toimii ympäristöissä missä GPS ei toimi. Visuaalinen odometria kehitettiin pyöräodometrian korvaajaksi, koska sen käyttö ei ole riippuvainen maastosta ja liikkumismuodosta. Tässä työssä tutkitaan ja kehitetään visuaalisen odometrian menetelmää reaaliaikaiseen sulautettuun järjestelmään. Työssä esitellään visuaalisen odometrian perusteet ja sen sisältämät osamenetelmät. Lisäksi esitellään yhtäaikainen paikallistaminen ja kartoitus (SLAM), jonka osana visuaalinen odometria voi esiintyä. Kehitettyä visuaalisen odometrian menetelmää on tarkoituksena käyttää Parrotin robottihelikopterille AR.Drone 2.0:lle tunnistamaan sen liikkeet. Tällöin robottihelikopteri saa tarpeeksi tietoa ympäristöstään lentääkseen itsenäisesti. Työssä toteutetaan algoritmi robotin tallentaman videomateriaalin tulkitsemiseen. Työssä toteutettu menetelmä on monokulaarinen SLAM, jossa käytetään yhden pisteen RANSAC-menetelmää yhdistettynä käänteisen syvyyden EKF:ään. Menetelmän piirteenirroitus ja vastinpisteiden etsintä korvataan reaaliaikaisella sulautetulle järjestelmälle sopivalla menetelmällä. Algoritmin toiminta testataan mittaamalla sen suoritusaika useilla kuvasekvensseillä ja analysoimalla sen piirtämää karttaa kameran liikkeestä. Lisäksi tarkastellaan sen antamien navigointitietojen todenmukaisuutta. Toteutetun järjestelmän toimintaa analysoidaan visuaalisesti ja sen toimintaa tarkastellaan suhteessa vertailumenetelmään. Työssä toteutettu visuaalisen odometrian menetelmä todetaan toimivaksi ratkaisuksi reaaliaikaiselle sulautetulle järjestelmälle tietyt rajoitukset huomioiden.Visual odometry is the process of estimating the motion of a vehicle, human or robot using the input of a single or multiple cameras. Application domains include robotics, wearable computing, augmented reality and automotive. It is a good supplement to the navigation systems because it operates in the environments where GPS does not. Visual odometry was developed as a substitute for wheel odometry, because its use is not dependent of the terrain. Visual odometry can be applied without restrictions to the way of movement (wheels, flying, walking). In this work visual odometry is examined and developed to be used in real-time embedded system. The basics of visual odometry are discussed. Furthermore, simultaneous localization and mapping (SLAM) is introduced. Visual odometry can appear as a part of SLAM. The purpose of this work is to develop visual odometry algorithm for Parrot’s robot helicopter AR.Drone 2.0, so it could fly independently in the future. The algorithm is based on Civera’s EKF-SLAM method, where feature extraction is replaced with an approach used earlier in global motion estimation. The operation of the algorithm is tested by measuring its performance time with different image sequences and by analyzing the movement of the camera from the map drawn by it. Furthermore, the reality of the navigation information is examined. The operation of the executed system is visually analyzed on the basis of the video and its operation is examined in relation to the comparison method. Developed visual odometry method is found to be a functional solution to the real-time embedded system under certain constraints