Hulya Gokalp

Monitoring Activities of Daily Living of the Elderly and the Potential for Its Use in Telecare and Telehealth: A Review

OBJECTIVE This review was designed to determine whether telemonitoring activities of daily living (ADL) of elderly people can improve quality of life and be beneficial to their healthcare. MATERIALS AND METHODS Electronic databases were searched for studies that monitored ADL of elderly people and preferably measured some clinical outcomes such as ability to predict key events that require intervention and for studies that assessed perception of elderly people of such telemonitoring systems. The articles were reviewed and assessed independently by two reviewers. RESULTS One hundred seventy-five unique studies were found. Sixty-seven of these were identified for potential inclusion, and 25 studies were finally included. Study characteristics, parameters monitored, outcomes, and problems encountered were summarized and discussed. The main focus was on the potential benefits of ADL monitoring on the care of elderly people. CONCLUSIONS Although most studies reported on technical improvements in methods for detecting changes in ADL, few, if any, determined the benefits to the patient of telemonitoring for changes in ADL or correlation with any physiological changes. We propose sensor and system characteristics for improved user acceptance and deployment in a large-scale care plan. We present areas requiring further investigation.

Designing effective visualizations of habits data to aid clinical decision making

BackgroundChanges in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data.MethodsOur approach to the design of the visualization follows User Centered Design, specifically, defining requirements, designing corresponding visualizations and finally evaluating results. This cycle was iterated three times.ResultsThe User Centered Design method was successfully employed to converge to a design that met the main objective of this study. The resulting visualizations of relevant features that were extracted from the sensor data were considered highly effective and intuitive to the clinicians and were considered suitable for monitoring the behavior patterns of patients.ConclusionsWe observed important differences in the approach and attitude of the researchers and clinicians. Whereas the researchers would prefer to have as many features and information as possible in each visualization, the clinicians would prefer clarity and simplicity, often each visualization having only a single feature, with several visualizations per page. In addition, concepts considered intuitive to the researchers were not always to the clinicians.

Dynamic Threshold Analysis of Daily Oxygen Saturation for Improved Management of COPD Patients.

This study presents a novel dynamic threshold algorithm that is applied to daily self-measured SpO2 data for management of chronic obstructive pulmonary disease (COPD) patients in remote patient monitoring to improve accuracy of detection of exacerbation. Conventional approaches based on a fixed threshold applied to a single SpO2 reading to detect deterioration in patient condition are known to have poor accuracy and result in high false alarm rates. This study develops and evaluates use of a dynamic threshold algorithm to reduce false alarm rates. Daily data from four COPD patients with a record of clinical interventions during the period were selected for analysis. We model the SpO2 timeseries data as a combination of a trend and a stochastic component (residual). We estimate the long-term trend using a locally weighed least-squares (low-pass) filter over a long-term processing window. Results show that the time evolution of the long-term trend indicated exacerbation with improved accuracy compared to a fixed threshold in our study population. Deterioration in the condition of a patient also resulted in an increase in the standard deviation of the residual (σres), from 2% or less when the patient is in a healthy condition to 4% or more when condition deteriorates. Statistical analysis of the residuals showed they had a normal distribution when the condition of the patient was stable but had a long tail on the lower side during deterioration.

Interoperable End-to-End Remote Patient Monitoring Platform Based on IEEE 11073 PHD and ZigBee Health Care Profile

This paper describes the implementation of an end-to-end remote monitoring platform based on the IEEE 11073 standards for personal health devices (PHD). It provides an overview of the concepts and approaches and describes how the standard has been optimized for small devices with limited resources of processor, memory, and power that use short-range wireless technology. It explains aspects of IEEE 11073, including the domain information model, state model, and nomenclature, and how these support its plug-and-play architecture. It shows how these aspects underpin a much larger ecosystem of interoperable devices and systems that include IHE PCD-01, HL7, and BlueTooth LE medical devices, and the relationship to the Continua Guidelines, advocating the adoption of data standards and nomenclature to support semantic interoperability between health and ambient assisted living in future platforms. The paper further describes the adaptions that have been made in order to implement the standard on the ZigBee Health Care Profile and the experiences of implementing an end-to-end platform that has been deployed to frail elderly patients with chronic disease(s) and patients with diabetes.

A randomised controlled trial to test the effectiveness of decision training on assessors' ability to determine optimal fitness-to-drive recommendations for older or disabled drivers.

BackgroundDriving licensing jurisdictions require detailed assessments of fitness-to-drive from occupational therapy driver assessors (OTDAs). We developed decision training based on the recommendations of expert OTDAs, to enhance novices’ capacity to make optimal fitness-to-drive decisions. The aim of this research was to determine effectiveness of training on novice occupational therapists’ ability to make fitness-to-drive decisions.MethodsA double blind, parallel, randomised controlled trial was conducted to test the effectiveness of decision training on novices’ fitness-to-drive recommendations. Both groups made recommendations on a series of 64 case scenarios with the intervention group receiving training after reviewing two thirds of the cases; the control group, at this same point, just received a message of encouragement to continue. Participants were occupational therapy students on UK and Australian pre-registration programmes who individually took part online, following the website instructions. The main outcome of training was the reduction in mean difference between novice and expert recommendations on the cases.ResultsTwo hundred eighty-nine novices were randomised into intervention; 166 completed the trial (70 in intervention; 96 in control). No statistical differences in scores were found pre-training. Post training, the control group showed no significant change in recommendations compared to the experts (t(96) = −.69; p = .5), whereas the intervention group exhibited a significant change (t(69) = 6.89; p < 0.001). For the intervention group, the mean difference compared with the experts’ recommendations reduced with 95% CI from −.13 to .09. Effect size calculated at the post-training demonstrated a moderate effect (d = .69, r = .32).ConclusionsNovices who received the decision training were able to change their recommendations whereas those who did not receive training did not. Those receiving training became more able to identify drivers who were not fit-to-drive, as measured against experts’ decisions on the same cases.This research demonstrated that novice occupational therapists can be trained to make decisions more aligned to those of expert OTDAs. The decision training and cases have been launched as a free training resource at www.fitnesstodrive.com. This can be used by novice driver assessors to increase their skill to identify drivers who are, and are not fit-to-drive, potentially increasing international workforce capacity in this growing field of practice.

Usage of minimum norm and wiener filter methods in the reduction of in-band interference

The aim of of this work is reduction of the in-band interference in the data obtained with the channel probe device in which the Frequency Modulated Continuous Wave (FMCW) signal is used. For this purpose, the minimum norm algorithm and Wiener filter applications were used. The results of examinations, by using more echoes of the channel profile, were compared and it was determined which method is better than the other. Also commented on the methods by calculating the channel variables.

Obtaining delay profiles with Pisarenko Harmonic Decomposition and Multiple Signal Classification method for FMCW channel data with in band interference

The aim of this study was to reduce the effect of in band interference in frequency modulated continuous wave (FMCW) channel data. In band interference increases noise floor in average power delay profile (APDP), i.e obscuring weaker multipath components. Pisarenko Harmonic Decomposition (PHD) and Multiple Signal Classification (MUSIC) Methods, which are subspace methods, enabled multipath components that were about 25 dB below the strongest components to be identified. Spurious peaks were observed in APDPs obtained with PHD and the weak echoes that could not be identified with FFT method, were identified with MUSIC.

Reducing effect of in band interference in FMCW channel data using Doppler pre-filtered prony modelling

The aim of this study is to reduce the effect of in band interference in frequency modulated continuous wave (FMCW) channel data. In band interference distorts the detector output of FMCW sounder which is normally sum of sinusoidal signals. This distortion causes abrupt fluctuation in time domain signal at the detector output and increases noise floor in average power delay profile (APDP). In this study Prony method with pre-filtering in Doppler domain was used to reduce the effect of in-band interference. The proposed method effectively reduced noise floor in APDP by more than 10 dB.

Analysis of daily oxygen saturation for detecting deterioration in the condition of COPD patients

This study presents a novel threshold algorithm that is applied to daily self-measured SpO2 data for management of COPD patients in remote patient monitoring to improve accuracy of detection of exacerbation. Conventional approaches based on a fixed threshold applied to a single SpO2 reading result in high false alarm rates. We model the SpO2 time series data as a combination of a trend and a stochastic component (residual) and use the standard deviation of residuals to identify exacerbations. Deterioration in the condition of a patient results in an increase in the standard deviation of the residual (σres), from 2% or less when the patient is in a healthy condition to 4% or more when the condition deteriorates. We present results from retrospective analysis of SpO2 data measured in patients with COPD as part of a long term project to monitor frail elderly, and compare results from the new approach with those from the conventional approach.

Whole population management of patients with diabetes

An increasingly aging population is presenting greater prevalence of people with diabetes, co-morbidities and the complications. Moreover, poor management of diabetes increases risk of complications. There is need to monitor these patients more closely to ensure optimum management. However current management is based on simple clinic based blood pressure and HbA1c readings, which prove insensitive to detect problems of lifestyle and habits. We therefore developed a platform that could be deployed to all diabetes patients to take daily blood pressure and blood glucose measurements that were sent automatically to the clinician. Data was reviewed after a two week monitoring period. Those that were deemed well controlled were asked to return the devices, which were cycled to the next patient. Others were asked to make an appointment with the clinician for review. 37% of patients required intervention. When stratified for risk using parameters from the EPR we found the greatest change in HbA1c in the low risk group, with the high risk group having little change. The greatest problem was denial in the recently diagnosed and lapse in others, resulting in poor adherence to medication and lifestyle.