Matching Items (2)
Filtering by
- All Subjects: Bluetooth Low Energy
- Creators: Angadi, Siddhartha
Description
Walking interventions focused on increasing step counts are typically associated with salutary effects on glycemia, fasting insulin, insulin resistance and blood lipids which may be in turn associated with improvements in cardiorespiratory fitness (peak oxygen uptake – VO2peak) and vascular stiffness. We hypothesized that a novel 4-month, behavioral economics-based walking intervention would have favorable effects on glucose homeostasis and blood lipids and that these in turn would be related to VO2peak and vascular stiffness (carotid femoral pulse wave velocity – cfPWV).
We carried out secondary analyses on a subsample of sedentary, overweight/obese adults who participated in a 4-month, 2x2, randomized-controlled walking intervention examining the effects of goal setting (static v. adaptive goals) and rewards (immediate v. delayed) on steps/day (N=96). Fasting blood samples (n=58) were collected from participants before and after the intervention. Premenopausal females were in the follicular phase of their menstrual cycles. Lipid and glucose levels were measured using an automated chemistry analyzer, while insulin was measured using radio-immunoassay. Homeostatic model of insulin resistance (HOMA-IR) was calculated using the following formula (HOMA-IR=glucose x insulin / 405). We examined associations [partial correlations (adjusted for age)] between changes in blood biomarkers and VO2peak and cfPWV, irrespective of group, and we used linear mixed models to examine between-group differences in levels of and change in biomarker outcomes.
Groups did not differ in overall levels of, or degree of change in, biomarker outcomes (all p>0.05). Mean changes, irrespective of group, in biomarkers were as follows: glucose Δ= 0.74± 4.5mg/dl; insulin Δ= 0.09 ± 4.1 µU/ml; total cholesterol Δ= 0.24 ± 20.6 mg/dl; HDL-C Δ= 0.27 ± 5.1 mg/dl; LDL-C Δ= 1.3 ± 19.9 mg/dl; triglycerides Δ= 1.7 ± 27.2 mg/dl; HOMA-IR Δ = -.0548 ± 1.05). We found no significant associations between change in biomarker levels and change in VO2peak or change in cfPWV (all correlation coefficients < 0.15; p > 0.05).
A 4-month, behavioral economics-based mHealth intervention focused on increasing steps/day did not bring about favorable changes on markers of glycemia, insulin resistance and blood lipids.
We carried out secondary analyses on a subsample of sedentary, overweight/obese adults who participated in a 4-month, 2x2, randomized-controlled walking intervention examining the effects of goal setting (static v. adaptive goals) and rewards (immediate v. delayed) on steps/day (N=96). Fasting blood samples (n=58) were collected from participants before and after the intervention. Premenopausal females were in the follicular phase of their menstrual cycles. Lipid and glucose levels were measured using an automated chemistry analyzer, while insulin was measured using radio-immunoassay. Homeostatic model of insulin resistance (HOMA-IR) was calculated using the following formula (HOMA-IR=glucose x insulin / 405). We examined associations [partial correlations (adjusted for age)] between changes in blood biomarkers and VO2peak and cfPWV, irrespective of group, and we used linear mixed models to examine between-group differences in levels of and change in biomarker outcomes.
Groups did not differ in overall levels of, or degree of change in, biomarker outcomes (all p>0.05). Mean changes, irrespective of group, in biomarkers were as follows: glucose Δ= 0.74± 4.5mg/dl; insulin Δ= 0.09 ± 4.1 µU/ml; total cholesterol Δ= 0.24 ± 20.6 mg/dl; HDL-C Δ= 0.27 ± 5.1 mg/dl; LDL-C Δ= 1.3 ± 19.9 mg/dl; triglycerides Δ= 1.7 ± 27.2 mg/dl; HOMA-IR Δ = -.0548 ± 1.05). We found no significant associations between change in biomarker levels and change in VO2peak or change in cfPWV (all correlation coefficients < 0.15; p > 0.05).
A 4-month, behavioral economics-based mHealth intervention focused on increasing steps/day did not bring about favorable changes on markers of glycemia, insulin resistance and blood lipids.
ContributorsHook, Benjamin E. (Author) / Angadi, Siddhartha (Thesis director) / Gaesser, Glenn (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Wearable technology has brought in a rapid shift in the areas of healthcare and lifestyle management. The recent development and usage of wearable devices like smart watches has created significant impact in areas like fitness management, exercise tracking, sleep quality assessment and early diagnosis of diseases like asthma, sleep apnea etc. This thesis is dedicated to the development of wearable systems and algorithms to fulfill unmet needs in the area of cardiorespiratory monitoring.
First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.
Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.
Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.
The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.
First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.
Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.
Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.
The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.
ContributorsTipparaju, Vishal Varun (Author) / Xian, Xiaojun (Thesis advisor) / Forzani, Erica (Thesis advisor) / Blain Christen, Jennifer (Committee member) / Angadi, Siddhartha (Committee member) / Arizona State University (Publisher)
Created2020