Cone-beam computed tomography (CBCT) dose optimization technique and image quality assessment scoring.

INTRODUCTION: Linear accelerator (LINAC) embedded with kV source-imager system is capable to do image-guided radiotherapy. The only disadvantage of cone-beam computed tomography image acquisition during treatment is the extra radiation dose to the patient. The aim of this study is to optimize the CBCT imaging doses likely to be received by the patient undergoing radiotherapy without affecting image quality. MATERIAL AND METHODS: The imaging dose to the patient was estimated on CTDI phantoms. The effect of additional filters of different materials (copper, brass, aluminum of thickness 0.1 mm each) was evaluated to find the optimized dose imaging technique. For the pelvis, a single imaging protocol available on the machine was used, whereas for the head and neck region, two protocols, high-quality head and standard-dose head were used. The image quality was assessed on CATPHAN-504 phantom using Owl CATPHAN® QA online tool. A new term "Image Assessment score" (IAS) was introduced to evaluate the image quality. RESULT: In the pelvis protocol, CBCT imaging doses with an additional 0.1-mm brass, copper, and aluminum filter were measured to be reduced by 7.1%, 4.7%, and 2.5%, respectively, whereas for high-quality head protocol, the dose reduction was 25.4% (with brass filter), 22% (with copper filter), and 3.1% (with aluminum filter). For the standard-dose head protocol, doses were reduced by 7.5%, 2.8%, and 2.1% with additional 0.1-mm brass copper and aluminum filters, respectively. Acceptable image quality was observed with all the filters. CONCLUSION: Although the reconstructed images were found somewhat noisier, they did not affect the purpose of imaging, that is, treatment position verification. It was observed that these extra filters further reduce the imaging dose without much affecting the image quality.

A multi-modal assessment of sleep stages using adaptive Fourier decomposition and machine learning.

Healthy sleep is essential for the rejuvenation of the body and helps in maintaining good health. Many people suffer from sleep disorders that are characterized by abnormal sleep patterns. Automated assessment of such disorders using biomedical signals has been an active subject of research. Electroencephalogram (EEG) is a popular diagnostic used in this regard. We consider a widely-used publicly available database and process the signals using the Fourier decomposition method (FDM) to obtain narrowband signal components. Statistical features extracted from these components are passed on to machine learning classifiers to identify different stages of sleep. A novel feature measuring the non-stationarity of the signal is also used to capture salient information. It is shown that classification results can be improved by using multi-channel EEG instead of single-channel EEG data. Simultaneous utilization of multiple modalities, such as Electromyogram (EMG), Electrooculogram (EOG) along with EEG data leads to further enhancement in the obtained results. The proposed method can be efficiently implemented in real-time using fast Fourier transform (FFT), and it provides better classification results than the other algorithms existing in the literature. It can assist in the development of low-cost sensor-based setups for continuous patient monitoring and feedback.

Sustainability assessment of hybrid active greenhouse solar dryer integrated with evacuated solar collector.

Environment and Economy are the two important pillars of sustainability. In this paper, the economic viability and environmental impact of the novel greenhouse dryer with an evacuated solar collector are calculated. For this analysis, tomato is dried inside the dryer as it is a high moisture crop that requires a faster drying rate otherwise it starts giving a bad odor and gets contaminated. The hybrid active greenhouse dryer is developed especially for drying high moisture agro and non-agro-based produce. Evacuated tube solar collector is integrated with the dryer that supplies the hot water to the heat exchanger kept inside the dryer. The hot water flowing inside the copper tubes of the heat exchanger transfers its heat to room air through convection and to crop through conduction. Hence the higher room temperature and faster moisture removal rate are obtained. Tomato slices have been dried from 94.6% (wb) to 10% (wb) moisture content in 10 h. The developed dryer can produce 261 kg of dried tomato annually and its payback time is only 1.73 years which is very less as compared to its life of 30 years. In its entire lifetime, the dryer will mitigate 169.10 tonnes of CO2 that prove its suitability from a sustainable point of view.

Is India ready for mental health apps (MHApps)? A quantitative-qualitative exploration of caregivers' perspective on smartphone-based solutions for managing severe mental illnesses in low resource settings.

BACKGROUND: Mobile application based delivery of psycho-social interventions may help reduce the treatment gap for severe mental illnesses (SMIs) and decrease the burden on caregivers. Apps developed in high income settings show effectiveness, but they suffer from lack of applicability in low resource scenarios due to the difference in technology penetration, affordability, and acceptance. OBJECTIVE: This study aimed to understand health technology usage, perceived needs, and acceptability of app based interventions in patients with SMIs to improve illness management and reduce caregiver burden. METHODS: The study was conducted in inpatient and outpatient settings of a tertiary care center in North India. A cross-sectional survey assessed smartphone and health app usage. Further, three focus group discussions evaluated the needs and apprehensions in using apps in management of SMIs. RESULTS: A total of 176 participants including 88 patients and 88 caregivers completed the survey. Smartphone ownership was similar to the national average (30%) in both caregivers (38.6%) and in patients (31.8%). Although subjects regularly used a third party app, health app usage was very low. Cost, unfamiliarity, and language were significant barriers to adoption. The focus group discussions provided insight into the various apprehensions of caregivers in using and in allowing patients to use smartphones and such apps. Caregivers wanted mobile apps for accessing information regarding services and resources available for people with SMI, and they felt such apps can be helpful if they could automate some of their routine caregiving activities. However, the significant difficulty was perceived in regards to the cost of the device, language of the medium, and unfamiliarity in using technology. Apprehensions that SMI patients might misuse technology, or damage the device were also prevalent. CONCLUSIONS: The study systematically looks into the scope, design considerations and limitations of implementing a mobile technology based intervention for low resource settings. With only one-third of the patients and caregivers having access to smartphones and internet, parallel outreach strategies like IVRS should be actively considered while designing interventions. The difficulty of understanding and searching in a non-native language needs to be addressed. Hand holding of caregivers and frequent encouragement from treating doctors might significantly help in technology adoption and in surmounting the apprehensions related to using technology. To make the solution acceptable and useful to the already over-burdened caregivers, developers need to work closely with patients' family members and follow a ground-up collaborative approach to app development. The scope of delivering mental health services through technology is immense in resource constrained settings like India, provided we, researchers, appreciate and accept the fact that in the varied landscape of a divergent economic, educational, and cultural milieu, a single solution will never suffice for all, and intervention modality matching with end user capacity will be of paramount importance in determining the success of the endeavor.

Socioeconomic patterns of underweight and its association with self-rated health, cognition and quality of life among older adults in India.

BACKGROUND: Underweight defined as body mass index (BMI) < 18.5 is associated with negative health and quality of life outcomes including mortality. Yet, little is known about the socioeconomic differentials in underweight and its association with health and well-being among older adults in India. This study examined the socioeconomic differentials in underweight among respondents aged ≥50 in India. Consequently, three outcomes of the association of underweight were studied. These are poor self-rated health, cognition and quality of life. METHODS: Cross-sectional data on 6,372 older adults derived from the first wave of the WHO's Study on global AGEing and adult health (SAGE), a nationally representative survey conducted in six states of India during 2007-8, were used. Bivariate and multivariate regression analyses were applied to fulfil the objectives. RESULTS: The overall prevalence of underweight was 38 percent in the study population. Further, socioeconomic status showed a significant and negative association with underweight. The association of underweight with poor self-rated health (OR = 1.60; p < .001), cognition (ß = -0.95; p < .001) and quality of life (ß = -1.90; p < .001) were remained statistically significant after adjusting for age, sex, place of residence, marital status, years of schooling, wealth quintile, sleep problems, chronic diseases, low back pain and state/province. CONCLUSION: The results indicated significant socioeconomic differentials in underweight and its association with poor self-rated health, cognition and quality of life outcomes. Interventions focussing on underweight older adults are important to enhance the overall wellbeing of the growing older population in India.

Access to healthcare among the Empowered Action Group (EAG) states of India: Current status and impeding factors.

BACKGROUND: Access to healthcare is crucial for meeting the health needs of Indians. We explored factors impeding access to public sources of healthcare among the Empowered Action Group (EAG) states of India. We also examined the extent to which Indians depend on public and private sources of healthcare in the EAG states. METHODS: Our study is based on the unit-level records of 9988 ailing persons, who were surveyed among the EAG states in the 71st round of the National Sample Survey (NSS), conducted during January-June 2014 on the theme 'Social consumption: Health'. To analyse the socioeconomic factors, we did logistic regression using STATA version 12.0. RESULTS: Despite a vast public health infrastructure in the EAG states, around three-fourths of inpatients are dependent on private sources of healthcare in both rural (70%) and urban (78%) areas. Poor quality and long waiting time in accessing healthcare from public health facilities remain big concerns for inpatients of the EAG states. CONCLUSION: To make public health services more accessible, there is a need to improve the quality of services, enlarge infrastructure to reduce waiting time, and enhance the physical reach to inpatients in the EAG states of India. Public health services will then be able to compete with those in the private sector.