Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects

The rapid development of technology has brought about a revolution in healthcare stimulating a wide range of smart and autonomous applications in homes, clinics, surgeries and hospitals. Smart healthcare opens the opportunity for a qualitative advance in the relations between healthcare providers and end-users for the provision of healthcare such as enabling doctors to diagnose remotely while optimizing the accuracy of the diagnosis and maximizing the benefits of treatment by enabling close patient monitoring. This paper presents a comprehensive review of non-invasive vital data acquisition and the Internet of Things in healthcare informatics and thus reports the challenges in healthcare informatics and suggests future work that would lead to solutions to address the open challenges in IoT and non-invasive vital data acquisition. In particular, the conducted review has revealed that there has been a daunting challenge in the development of multi-frequency vital IoT systems, and addressing this issue will help enable the vital IoT node to be reachable by the broker in multiple area ranges. Furthermore, the utilization of multi-camera systems has proven its high potential to increase the accuracy of vital data acquisition, but the implementation of such systems has not been fully developed with unfilled gaps to be bridged. Moreover, the application of deep learning to the real-time analysis of vital data on the node/edge side will enable optimal, instant offline decision making. Finally, the synergistic integration of reliable power management and energy harvesting systems into non-invasive data acquisition has been omitted so far, and the successful implementation of such systems will lead to a smart, robust, sustainable and self-powered healthcare system

Bone mineral density, body mass index and cigarette smoking among Iranian women: implications for prevention

BACKGROUND: While risk factors of osteoporosis in Western populations have been extensively documented, such a profile has not been well studied in Caucasians of non-European origin. This study was designed to estimate the modifiable distribution and determinants of bone mineral density (BMD) among Iranian women in Australia. METHODS: Ninety women aged 35 years and older completed a questionnaire on socio-demographic and lifestyle factors. BMD was measured at the lumbar spine (LS) and femoral neck (FN) using DXA (GE Lunar, WI, USA), and was expressed in g/cm(2 )as well as T-score. RESULTS: In multiple regression analysis, advancing age, lower body mass index (BMI), and smoking were independently associated with LS and FN BMD, with the 3 factors collectively accounting for 30% and 38% variance of LS and FN BMD, respectively. LS and FN BMD in smokers was 8% lower than that in non-smokers. Further analysis of interaction between BMI and smoking revealed that the effect of smoking was only observed in the obese group (p = 0.029 for LSBMD and p = 0.007 for FNBMD), but not in the overweight and normal groups. Using T-scores from two bone sites the prevalence of osteoporosis (T-scores ≤ -2.5) was 3.8% and 26.3% in pre-and post-menopausal women, respectively. Among current smokers, the prevalence was higher (31.3%) than that among ex-smokers (28.6%) and non-smokers (7.5%). CONCLUSION: These data, for the first time, indicate that apart from advancing age and lower body mass index, cigarette smoking is an important modifiable determinant of bone mineral density in these Caucasians of non-European origin

Effect of physical activity intervention based on a pedometer on physical activity level and anthropometric measures after childbirth: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Pregnancy and childbirth are associated with weight gain in women, and retention of weight gained during pregnancy can lead to obesity in later life. Diet and physical activity are factors that can influence the loss of retained pregnancy weight after birth. Exercise guidelines exist for pregnancy, but recommendations for exercise after childbirth are virtually nonexistent. The aim of this study was to evaluate the effect of physical activity intervention based on pedometer on physical activity level and anthropometric measures of women after childbirth.</p> <p>Methods</p> <p>We conducted a randomized controlled trial in which 66 women who had given birth 6 weeks to 6 months prior were randomly assigned to receive either a 12 week tailored program encouraging increased walking using a pedometer (intervention group, n = 32) or routine postpartum care (control group, n = 34). During the 12-week study period, each woman in the intervention group wore a pedometer and recorded her daily step count. The women were advised to increase their steps by 500 per week until they achieved the first target of 5000 steps per day and then continued to increase it to minimum of 10,000 steps per day by the end of 12^thweek. Assessed outcomes included anthropometric measures, physical activity level, and energy expenditure per week. Data were analyzed using the paired t-test, independent t-test, Mann-Whitney, chi-square, Wilcoxon, covariance analysis, and the general linear model repeated measures procedure as appropriate.</p> <p>Results</p> <p>After 12 weeks, women in the intervention group had significantly increased their physical activity and energy expenditure per week (4394 vs. 1651 calorie, <it>p </it>< 0.001). Significant differences between-group in weight (<it>P </it>= 0.001), Body Mass Index (<it>P </it>= 0.001), waist circumference (<it>P </it>= 0.001), hip circumference (<it>P </it>= 0.032) and waist-hip ratio (<it>P </it>= 0.02) were presented after the intervention. The intervention group significantly increased their mean daily step count over the study period (from 3249 before, to 9960 after the intervention, <it>p </it>< 0.001).</p> <p>Conclusion</p> <p>A physical activity intervention based on pedometer is an effective means to increase physical activity; reducing retention of weight gained during pregnancy and can improve anthropometric measures in postpartum women.</p> <p>Trial registration</p> <p>ISRCTN: <a href="http://www.controlled-trials.com/IRCT201105026362N1">IRCT201105026362N1</a></p

Arcuate Fasciculus Abnormalities and Their Relationship with Psychotic Symptoms in Schizophrenia

Disruption of fronto-temporal connections involving the arcuate fasciculus (AF) may underlie language processing anomalies and psychotic features such as auditory hallucinations in schizophrenia. No study to date has specifically investigated abnormalities of white matter integrity at particular loci along the AF as well as its regional lateralization in schizophrenia. We examined white matter changes (fractional anisotropy (FA), axial diffusivity (AD), asymmetry indices) along the whole extent of the AF and their relationship with psychotic symptoms in 32 males with schizophrenia and 44 healthy males. Large deformation diffeomorphic metric mapping and Fiber Assignment Continuous Tracking were employed to characterize FA and AD along the geometric curve of the AF. Our results showed that patients with schizophrenia had lower FA in the frontal aspects of the left AF compared with healthy controls. Greater left FA and AD lateralization in the temporal segment of AF were associated with more severe positive psychotic symptoms such as delusions and hallucinations in patients with schizophrenia. Disruption of white matter integrity of the left frontal AF and accentuation of normal left greater than right asymmetry of FA/AD in the temporal AF further support the notion of aberrant fronto-temporal connectivity in schizophrenia. AF pathology can affect corollary discharge of neural signals from frontal speech/motor initiation areas to suppress activity of auditory cortex that may influence psychotic phenomena such as auditory hallucinations and facilitate elaboration of delusional content

A Patient-Specific 3D Model for Port Placement in Robotic Surgery

International audiencePort placement is a critical task in robotic laparoscopy surgery. A method for determining optimal port placement is proposed. A patient-specific 3D model of the abdomen was created from 3D images taken by a 3D scanner in the operating room and pre-operative medical images. Using the patient-specific 3D model, and the robot arms' configurations, the accessible 3D points (on the abdominal surface) for one robot arm were calculated. The possible port locations (as 3D points) were selected based on a performance index that is obtained from the outputs of an inverse kinematic problem. Repeating the process for the other robotic arms is expected to yield a set of optimal port locations for the individual patient

A Patient-Specific 3D Model for Port Placement in Robotic Surgery

International audiencePort placement is a critical task in robotic laparoscopy surgery. A method for determining optimal port placement is proposed. A patient-specific 3D model of the abdomen was created from 3D images taken by a 3D scanner in the operating room and pre-operative medical images. Using the patient-specific 3D model, and the robot arms' configurations, the accessible 3D points (on the abdominal surface) for one robot arm were calculated. The possible port locations (as 3D points) were selected based on a performance index that is obtained from the outputs of an inverse kinematic problem. Repeating the process for the other robotic arms is expected to yield a set of optimal port locations for the individual patient

A Prototype Representation to Approximate White Matter Bundles with Weighted Currents

International audienceQuantitative and qualitative analysis of white matter fibers resulting from tractography algorithms is made difficult by their huge number. To this end, we propose an \textit{approximation scheme} which gives as result a more concise but at the same time exhaustive representation of a fiber bundle. It is based on a novel computational model for fibers, called \textit{weighted currents}, characterised by a metric that considers both the pathway and the anatomical locations of the endpoints of the fibers. Similarity has therefore a twofold connotation: geometrical and related to the connectivity. The core idea is to use this metric for approximating a fiber bundle with a set of weighted prototypes, chosen among the fibers, which represent ensembles of similar fibers. The weights are related to the number of fibers represented by the prototypes. The algorithm is divided into two steps. First, the main modes of the fiber bundle are detected using a \textit{modularity based clustering} algorithm. Second, a \textit{prototype fiber selection} process is carried on in each cluster separately. This permits to explain the main patterns of the fiber bundle in a fast and accurate way