Predictive regression modeling of body segment parameters using individual-based anthropometric measurements

Body Segment Parameters

Predictive factors of glycosylated hemoglobin using additive regression model

Introduction: Diabetes is a chronic disease, non-epidemic disease that costs a lot of money in each year. One of the diagnostic criteria for diabetes is Glycosylated Hemoglobin (HBA1C), which in this study the effective factors on it examined by additive regression model. Materials and Methods: In this cross-sectional study, 130 patients with diabetes type-2 were selected based on simple random...

Hrtf Personalization Using Anthropometric Measurements

Individualized head related transfer functions (HRTFs) are needed for accurate rendering of spatial audio, which is important in many applications. Since these are relatively tedious to acquire, they may not be acceptable for some applications. A number of studies have sought to perform simple customization of the HRTF. We propose and test a strategy for HRTF personalization, based on matching ...

Body Fat Percentage in Active and Inactive Students Using Anthropometric Parameters

Introduction: Complications of obesity and high fat in children are grave now and future. The aim of this research is comparing percentage of body fat in active and inactive girls using Anthropometric Parameters.Materials and Methods: This research is descriptive- correlation that 144 active(n= 70) and inactive(n= 74) girls aged 8 to 10 years old were selected by random cluster sampling method ...

Anthropometric parameters--predictive factors for cardio-metabolic diseases.

UNLABELLED The aim of this study was to evaluate comparatively the predictive power of body mass index (BMI) and waist circumference (WC), two anthropometric parameters used in daily practice, for detecting cardio-metabolic diseases, in a rural community in north-east Romania. MATERIAL AND METHODS We evaluated 3248 persons, aged 19 or over, for whom we collected the following data: medical hi...