Justin Boyle

Automatic Detection of Respiration Rate From Ambulatory Single-Lead ECG

Ambulatory electrocardiography is increasingly being used in clinical practice to detect abnormal electrical behavior of the heart during ordinary daily activities. The utility of this monitoring can be improved by deriving respiration, which previously has been based on overnight apnea studies where patients are stationary, or the use of multilead ECG systems for stress testing. We compared six respiratory measures derived from a single-lead portable ECG monitor with simultaneously measured respiration air flow obtained from an ambulatory nasal cannula respiratory monitor. Ten controlled 1-h recordings were performed covering activities of daily living (lying, sitting, standing, walking, jogging, running, and stair climbing) and six overnight studies. The best method was an average of a 0.2-0.8 Hz bandpass filter and RR technique based on lengthening and shortening of the RR interval. Mean error rates with the reference gold standard were plusmn4 breaths per minute (bpm) (all activities), plusmn2 bpm (lying and sitting), and plusmn1 breath per minute (overnight studies). Statistically similar results were obtained using heart rate information alone (RR technique) compared to the best technique derived from the full ECG waveform that simplifies data collection procedures. The study shows that respiration can be derived under dynamic activities from a single-lead ECG without significant differences from traditional methods.

Wavelet based approach for posture transition estimation using a waist worn accelerometer

The ability to rise from a chair is considered to be important to achieve functional independence and quality of life. This sit-to-stand task is also a good indicator to assess condition of patients with chronic diseases. We developed a wavelet based algorithm for detecting and calculating the durations of sit-to-stand and stand-to-sit transitions from the signal vector magnitude of the measured acceleration signal. The algorithm was tested on waist worn accelerometer data collected from young subjects as well as geriatric patients. The test demonstrates that both transitions can be detected by using wavelet transformation applied to signal magnitude vector. Wavelet analysis produces an estimate of the transition pattern that can be used to calculate the transition duration that further gives clinically significant information on the patients condition. The method can be applied in a real life ambulatory monitoring system for assessing the condition of a patient living at home.

Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block

To investigate the effect of hospital occupancy levels on inpatient and ED patient flow parameters, and to simulate the impact of shifting discharge timing on occupancy levels.

The National Emergency Access Target (NEAT) and the 4-hour rule: time to review the target.

Objective: We explored the relationship between the National Emergency Access Target (NEAT) compliance rate, defined as the proportion of patients admitted or discharged from emergency departments (EDs) within 4 hours of presentation, and the risk‐adjusted in‐hospital mortality of patients admitted to hospital acutely from EDs.

Challenges in digital imaging for artificial human vision

Several international research teams are currently developing artificial human vision systems that have the potential to restore some visual faculties to blind persons. Given the significant advancements from these teams, it is conceivable that the implantation of a safe a d useful prosthesis will occur soon, perhaps in the next 2-4 years. It is thus timely to suggest and demonstrate methods to increase the information content of such artificial vision systems. Several ideas are suggested in this paper, such as brightness modulation, range indication, importance mapping and the delivery of supplementary information, which will do much towards providing visual information comparable to that obtained via a normally functioning human eye but at far lower information rates. This paper briefly describes the framework of artificial vision systems and outlines basic considerations of digital image processing as applied to artificial vision systems. We describe the poor quality of anticipated images produced by these artificial vision systems and the need for enhancing the images to allow increased scene understanding. Several techniques are identified which could enhance the information content of images. We then describe our own research in this area, which aims to determines the performance envelope of useful low quality images associated with artificial vision systems. Our subjective assessment studies using representative test patterns have investigated how much information and what types of information are needed to recognize or perceive a scene. This testing has been to identify the most informative image processing operations which lead to better understanding of picture content.

New emergency department quality measure: from access block to National Emergency Access Target compliance.

The study aims to investigate the effect of time of day and ED occupancy on the ability of EDs to admit or discharge patients within 4 h in accordance with the National Emergency Access Target (NEAT), and to compare this with corresponding levels of access block, the measure for ED performance before NEAT.

Quantifying Functional Mobility Progress for Chronic Disease Management

A method for quantifying improvements in functional mobility is presented based on patient-worn accelerometer devices. For patients with cardiovascular, respiratory, or other chronic disease, increasing the amount of functional mobility is a large component of rehabilitation programs. We have conducted an observational trial on the use of accelerometers for quantifying mobility improvements in a small group of chronic disease patients (n=15, 48 - 86 yrs). Cognitive impairments precluded complex instrumentation of patients, and movement data was obtained from a single 2-axis accelerometer device worn at the hip. In our trial, movement data collected from accelerometer devices was classified into Lying vs Sitting/Standing vs Walking/Activity movements. This classification enabled the amount of walking to be quantified and graphically presented to clinicians and carers for feedback on exercise efficacy. Presenting long term trends in this data to patients also provides valuable feedback for self managed care and assisting with compliance

Scene specific imaging for bionic vision implants

Progress within the field of bionic vision (visual prosthesis) implants is at clinical trial stage, with several blind patients fitted with implanted vision systems, in this paper we suggest the image processing required for these devices is adjusted depending on the scene type. Characteristics of simple scenes are listed along with image processing techniques required to best present information from that scene type.

Static image simulation of electronic visual prostheses

The development of electronic visual prostheses (artificial human vision/bionic eye systems) is steadily progressing due to the combined efforts of several international research teams. In order to anticipate informative image processing strategies that could be used in these prostheses systems, we have undertaken psychophysical testing using low quality images to simulate visual representation associated with electronic visual prostheses. Our objective is to investigate how much information and what types of information are needed to recognise or perceive a scene, when most of the original scene data is lost. This paper describes results from testing of 174 normally sighted subjects who viewed a set of low quality (low spatial resolution and low grey-scale) static images. These experiments have identified informative image processing operations which can improve understanding of picture content.

Discharge timeliness and its impact on hospital crowding and emergency department flow performance.

The objective of this research is to identify optimal inpatient discharge time targets to help hospitals reduce crowding, improve patient flow through the ED and balance staff workload.