Integration of electroencephalogram (EEG) and motion tracking sensors for objective measure of attention-deficit hyperactivity disorder (MAHD) in pre-schoolers.

We developed an integrated device composed of a single-probe Electroencephalogram (EEG) and Charge Coupled Device (CCD) based motion sensors for objective measurement of Attention-deficit Hyperactivity Disorder (ADHD). While the measurement of attention-deficit hyperactivity disorder (MAHD) relies on the EEG signal for the assessment of attention during a given structured task, the CCD sensor depicts the movement pattern of the subjects engaged in a continuous performance task. A statistical analysis of attention and movement patterns was performed, and the accuracy of completed tasks was analyzed using indigenously developed software. The device with the embedded software is intended to improve certainty with criterion E. We used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 year old pre-schoolers). During the performance of the task power for delta and beta, EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task. We used our indigenously developed software for statistical analysis to derive a scale for the objective assessment of ADHD. We also compared our scale with clinical ADHD evaluations and found a significant correlation between the objective assessment of the ADHD subjects and the clinician's conventional evaluation. MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Active Case Finding for Tuberculosis through TOUCH Agents in Selected High TB Burden Wards of Kolkata, India: A Mixed Methods Study on Outcomes and Implementation Challenges.

Active case finding (ACF) for tuberculosis (TB) was implemented in 60 selected high TB burden wards of Kolkata, India. Community volunteers called TOUCH (Targeted Outreach for Upliftment of Community Health) agents (TAs) identified and referred presumptive TB patients (PTBPs) to health facilities for TB diagnosis and treatment. We aimed to describe the "care cascade" of PTBPs that were identified during July to December 2018 and to explore the reasons for attrition as perceived by TAs and PTBPs. An explanatory mixed-methods study with a quantitative phase of cohort study using routinely collected data followed by descriptive qualitative study with in-depth interviews was conducted. Of the 3,86242 individuals that were enumerated, 1132 (0.3%) PTBPs were identified. Only 713 (63.0%) PTBPs visited a referred facility for TB diagnosis. TB was diagnosed in 177 (24.8%). The number needed to screen for one TB patient was 2183 individuals. The potential reasons for low yield were stigma and apprehension about TB, distrust about TA, wage losses for attending health facilities, and substance abuse among PTBPs. The yield of ACF was suboptimal with low PTBP identification rate and a high attrition rate. Interviewing each individual for symptoms of TB and supporting PTBPs for diagnosis through sputum collection and transport can be adopted to improve the yield.