Niranjan Bidargaddi

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.

Detecting walking activity in cardiac rehabilitation by using accelerometer

This study is part of the ongoing care assessment platform project, which involves monitoring vital signs and daily activity profile information of chronic disease patients undergoing cardiac rehabilitation. In this study, we have focussed on detecting walking activity from a cardiac rehab session which includes many other high intensity activities such as biking and rowing, using waist worn accelerometers. Walking is an important measure useful to assess the mobility of elderly people. Various methods have been proposed in the literature to identify walking from waist worn accelerometer signals based on wavelet, frequency and computational intelligence methods. Wavelet based approach, due to its feasibility to be implemented in real time with low computational complexity, good accuracies and also the ability to provide good time frequency resolution, has been the most desirable approach. In this study, we have evaluated and compared six wavelet decomposition based measures to detect walk from other high intensity activities. The different measures were derived using anterior-posterior, vertical, medio-lateral and signal vector magnitude (SVM) acceleration signals. The results show that all these measures can discriminate walking from other high intensity activities and the SVM based measure was the most efficient (89.14% sensitivity and 89.97 % specificity).

Participatory Research as One Piece of the Puzzle: A Systematic Review of Consumer Involvement in Design of Technology-Based Youth Mental Health and Well-Being Interventions

Background Despite the potential of technology-based mental health interventions for young people, limited uptake and/or adherence is a significant challenge. It is thought that involving young people in the development and delivery of services designed for them leads to better engagement. Further research is required to understand the role of participatory approaches in design of technology-based mental health and well-being interventions for youth. Objective To investigate consumer involvement processes and associated outcomes from studies using participatory methods in development of technology-based mental health and well-being interventions for youth. Methods Fifteen electronic databases, using both resource-specific subject headings and text words, were searched describing 2 broad concepts-participatory research and mental health/illness. Grey literature was accessed via Google Advanced search, and relevant conference Web sites and reference lists were also searched. A first screening of titles/abstracts eliminated irrelevant citations and documents. The remaining citations were screened by a second reviewer. Full text articles were double screened. All projects employing participatory research processes in development and/or design of (ICT/digital) technology-based youth mental health and well-being interventions were included. No date restrictions were applied; English language only. Data on consumer involvement, research and design process, and outcomes were extracted via framework analysis. Results A total of 6210 studies were reviewed, 38 full articles retrieved, and 17 included in this study. It was found that consumer participation was predominantly consultative and consumerist in nature and involved design specification and intervention development, and usability/pilot testing. Sustainable participation was difficult to achieve. Projects reported clear dichotomies around designer/researcher and consumer assumptions of effective and acceptable interventions. It was not possible to determine the impact of participatory research on intervention effectiveness due to lack of outcome data. Planning for or having pre-existing implementation sites assisted implementation. The review also revealed a lack of theory-based design and process evaluation. Conclusions Consumer consultations helped shape intervention design. However, with little evidence of outcomes and a lack of implementation following piloting, the value of participatory research remains unclear.

An eHealth Intervention for Patients in Rural Areas: Preliminary Findings From a Pilot Feasibility Study

Background eHealth facilitation of chronic disease management has potential to increase engagement and effectiveness and extend access to care in rural areas. Objective The objective of this study was to demonstrate the feasibility and acceptability of an eHealth system for the management of chronic conditions in a rural setting. Methods We developed an online management program which incorporated content from the Flinders Chronic Condition Management Program (Flinders Program) and used an existing software platform (goACT), which is accessible by patients and health care workers using either Web-enabled mobile phone or Internet, enabling communication between patients and clinicians. We analyzed the impact of this eHealth system using qualitative and simple quantitative methods. Results The eHealth system was piloted with 8 recently hospitalized patients from rural areas, average age 63 (SD 9) years, each with an average of 5 chronic conditions and high level of psychological distress with an average K10 score of 32.20 (SD 5.81). Study participants interacted with the eHealth system. The average number of logins to the eHealth system by the study participants was 26.4 (SD 23.5) over 29 weeks. The login activity was higher early in the week. Conclusions The pilot demonstrated the feasibility of implementing and delivering a chronic disease management program using a Web-based patient-clinician application. A qualitative analysis revealed burden of illness and low levels of information technology literacy as barriers to patient engagement.

A Comparison Between Phone-Based Psychotherapy With and Without Text Messaging Support In Between Sessions for Crisis Patients

Background Few studies have tested whether individually tailored text messaging interventions have an effect on clinical outcomes when used to supplement traditional psychotherapy. This is despite the potential to improve outcomes through symptom monitoring, prompts for between-session activities, and psychoeducation. Objective The intent of the study was to explore the use of individually tailored between-session text messaging, or short message service (SMS), as an adjunct to telephone-based psychotherapy for consumers who present to the Emergency Department (ED) in situational and/or emotional crises. Methods Over a 4-month period, two therapists offered 68 prospective consumers of a telephone-based psychotherapy service individually tailored between-session text messaging alongside their telephone-based psychotherapy. Attendance and clinical outcomes (depression, anxiety, functional impairment) of those receiving messages were compared against a historical control group (n=157) who received telephone psychotherapy only. Results A total of 66% (45/68) of the consumers offered SMS accepted the intervention. A total of 432 messages were sent over the course of the trial, the majority involving some kind of psychoeducation or reminders to engage in therapy goals. There were no significant differences in clinical outcomes between consumers who received the SMS and those in the control group. There was a trend for participants in the intervention group to attend fewer sessions than those in the control group (mean 3.7, SD 1.9 vs mean 4.4, SD 2.3). Conclusions Both groups showed significant improvement over time. Individually tailored SMS were not found to improve clinical outcomes in consumers receiving telephone-based psychotherapy, but the study was underpowered, given the effect sizes noted and the significance level chosen. Given the ease of implementation and positive feedback from therapists and clients, individually tailored text messages should be explored further in future trials with a focus on enhancing the clinical impact of the tailored text messages, and utilizing designs with additional power to test for between-group effects.

Combining segmental semi-Markov models with neural networks for protein secondary structure prediction

Motivation: Predicting the secondary structure of proteins from a primary sequence alone has been variously approached from either a classification or a generative model perspective. The most prominent classification methods have used neural networks, which involves mappings from a local window of residues in the sequence to the structural state of the central residue in the window, thus capturing the local interactions effectively. However, they fail to capture distant interactions among residues. The generative models based on Bayesian segmentation capture sequence structure relationships using generalized hidden Markov models with explicit state duration. They capture non-local interactions through a joint sequence-structure probability distribution based on structural segments. In this paper, we investigate a combined architecture of Bayesian segmentation at the first stage and neural network at the second stage which captures both local and non-local correlation, to increase the single sequence prediction accuracy. The combined architecture is further enhanced by using neural network optimization and ensemble techniques. Results: The proposed architecture has been built and tested on two widely studied databases comprising 480 and 608 protein sequences, respectively. It achieved accuracies of above 71%, which is comparable to the highest accuracies reported so far for single sequence methods, without using the evolutionary information provided by multiple sequence alignments. The required data sets and program codes are available at http://www.gippsland.monash.edu.au/research/publish/neurocomputing.zip.

Mental Health Technologies: Designing With Consumers

Despite growing interest in the promise of e-mental and well-being interventions, little supporting literature exists to guide their design and the evaluation of their effectiveness. Both participatory design (PD) and design thinking (DT) have emerged as approaches that hold significant potential for supporting design in this space. Each approach is difficult to definitively circumscribe, and as such has been enacted as a process, a mind-set, specific practices/techniques, or a combination thereof. At its core, however, PD is a design research tradition that emphasizes egalitarian partnerships with end users. In contrast, DT is in the process of becoming a management concept tied to innovation with strong roots in business and education. From a health researcher viewpoint, while PD can be reduced to a number of replicable stages that involve particular methods, techniques, and outputs, projects often take vastly different forms and effective PD projects and practice have traditionally required technology-specific (eg, computer science) and domain-specific (eg, an application domain, such as patient support services) knowledge. In contrast, DT offers a practical off-the-shelf toolkit of approaches that at face value have more potential to have a quick impact and be successfully applied by novice practitioners (and those looking to include a more human-centered focus in their work). Via 2 case studies we explore the continuum of similarities and differences between PD and DT in order to provide an initial recommendation for what health researchers might reasonably expect from each in terms of process and outcome in the design of e-mental health interventions. We suggest that the sensibilities that DT shares with PD (ie, deep engagement and collaboration with end users and an inclusive and multidisciplinary practice) are precisely the aspects of DT that must be emphasized in any application to mental health provision and that any technology development process must prioritize empathy and understanding over innovation for the successful uptake of technology in this space.

Digital footprints: Facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies

Digital footprints, the automatically accumulated by-products of our technology-saturated lives, offer an exciting opportunity for psychiatric research. The commercial sector has already embraced the electronic trails of customers as an enabling tool for guiding consumer behaviour, and analogous efforts are ongoing to monitor and improve the mental health of psychiatric patients. The untargeted collection of digital footprints that may or may not be health orientated comprises a large untapped information resource for epidemiological scale research into psychiatric disorders. Real-time monitoring of mood, sleep and physical and social activity in a substantial portion of the affected population in a naturalistic setting is unprecedented in psychiatry. We propose that digital footprints can provide these measurements from real world setting unobtrusively and in a longitudinal fashion. In this perspective article, we outline the concept of digital footprints and the services and devices that create them, and present examples where digital footprints have been successfully used in research. We then critically discuss the opportunities and fundamental challenges associated digital footprints in psychiatric research, such as collecting data from different sources, analysis, ethical and research design challenges.

The promise and the reality: a mental health workforce perspective on technology-enhanced youth mental health service delivery

BackgroundDigital technologies show promise for reversing poor engagement of youth (16–24 years) with mental health services. In particular, mobile and internet based applications with communication capabilities can augment face-to-face mental health service provision. The literature in this field, however, fails to adequately capture the perspectives of the youth mental health workforce regarding utility and acceptability of technology for this purpose.MethodsThis paper describes results of in-depth qualitative data drawn from various stakeholders involved in provision of youth mental health services in one Australian rural region. Data were obtained using focus groups and semi-structured interviews with regional youth mental health clinicians, youth workers and support/management staff (n = 4 focus groups; n = 8 interviews) and analysed via inductive thematic analysis.ResultsResults question the acceptability of technology to engage clients within youth mental health services. Six main themes were identified: young people in a digital age, personal connection, power and vulnerability, professional identity, individual factors and organisational legitimacy.ConclusionsThese findings deepen the understanding of risks and challenges faced when adopting new technologies in mental healthcare. Recommendations for technology design and implementation in mental health services are made.