GymCam

Worn sensors are popular for automatically tracking exercises. However, a wearable is usually attached to one part of the body, tracks only that location, and thus is inadequate for capturing a wide range of exercises, especially when other limbs are involved. Cameras, on the other hand, can fully track a user's body, but suffer from noise and occlusion. We present GymCam, a camera-based system for automatically detecting, recognizing and tracking multiple people and exercises simultaneously in unconstrained environments without any user intervention. We collected data in a varsity gym, correctly segmenting exercises from other activities with an accuracy of 84.6%, recognizing the type of exercise at 93.6% accuracy, and counting the number of repetitions to within ± 1.7 on average. GymCam advances the field of real-time exercise tracking by filling some crucial gaps, such as tracking whole body motion, handling occlusion, and enabling single-point sensing for a multitude of users.</jats:p

CRISPR/Cas9 screen in human iPSC‐derived cortical neurons identifies NEK6 as a novel disease modifier of C9orf72 poly(PR) toxicity

Introduction The most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are hexanucleotide repeats in chromosome 9 open reading frame 72 (C9orf72). These repeats produce dipeptide repeat proteins with poly(PR) being the most toxic one. Methods We performed a kinome-wide CRISPR/Cas9 knock-out screen in human induced pluripotent stem cell (iPSC) -derived cortical neurons to identify modifiers of poly(PR) toxicity, and validated the role of candidate modifiers using in vitro, in vivo, and ex-vivo studies. Results Knock-down of NIMA-related kinase 6 (NEK6) prevented neuronal toxicity caused by poly(PR). Knock-down of nek6 also ameliorated the poly(PR)-induced axonopathy in zebrafish and NEK6 was aberrantly expressed in C9orf72 patients. Suppression of NEK6 expression and NEK6 activity inhibition rescued axonal transport defects in cortical neurons from C9orf72 patient iPSCs, at least partially by reversing p53-related DNA damage. Discussion We identified NEK6, which regulates poly(PR)-mediated p53-related DNA damage, as a novel therapeutic target for C9orf72 FTD/ALS

Illness Mapping: A time and cost effective method to estimate healthcare data needed to establish community-based health insurance

Background: Most healthcare spending in developing countries is private out-of-pocket. One explanation for low penetration of health insurance is that poorer individuals doubt their ability to enforce insurance contracts. Community-based health insurance schemes (CBHI) are a solution, but launching CBHI requires obtaining accurate local data on morbidity, healthcare utilization and other details to inform package design and pricing. We developed the "Illness Mapping" method (IM) for data collection (faster and cheaper than household surveys). Methods. IM is a modification of two non-interactive consensus group methods (Delphi and Nominal Group Technique) to operate as interactive methods. We elicited estimates from "Experts" in the target community on morbidity and healthcare utilization. Interaction between facilitator and experts became essential to bridge literacy constraints and to reach consensus.The study was conducted in Gaya District, Bihar (India) during April-June 2010. The intervention included the IM and a household survey (HHS). IM included 18 women's and 17 men's groups. The HHS was conducted in 50 villages with1,000 randomly selected households (6,656 individuals). Results: We found good agreement between the two methods on overall prevalence of illness (IM: 25.9% ±3.6; HHS: 31.4%) and on prevalence of acute (IM: 76.9%; HHS: 69.2%) and chronic illnesses (IM: 20.1%; HHS: 16.6%). We also found good agreement on incidence of deliveries (IM: 3.9% ±0.4; HHS: 3.9%), and on hospital deliveries (IM: 61.0%. ± 5.4; HHS: 51.4%). For hospitalizations, we obtained a lower estimate from the IM (1.1%) than from the HHS (2.6%). The IM required less time and less person-power than a household survey, which translate into reduced costs. Conclusions: We have shown that our Illness Mapping method can be carried out at lower financial and human cost for sourcing essential local data, at acceptably accurate levels. In view of the good fit of results obtained, we assume that the method could work elsewhere as well

Practical and Rich User Digitization

A long-standing vision in computer science has been to evolve computing devices into proactive assistants that enhance our productivity, health and wellness, and many other facets of our lives. User digitization is crucial in achieving this vision as it allows computers to intimately understand their users, capturing activity, pose, routine, and behavior. Today’s consumer devices – like smartphones and smartwatches – provide a glimpse of this potential, offering coarse digital representations of users with metrics such as step count, heart rate, and a handful of human activities like running and biking. Even these very low-dimensional representations are already bringing value to millions of people’s lives, but there is significant potential for improvement. On the other end, professional, high-fidelity comprehensive user digitization systems exist. For example, motion capture suits and multi-camera rigs that digitize our full body and appearance, and scanning machines such as MRI capture our detailed anatomy. However, these carry significant user practicality burdens, such as financial, privacy, ergonomic, aesthetic, and instrumentation considerations, that preclude consumer use. In general, the higher the fidelity of capture, the lower the user’s practicality. Most conventional approaches strike a balance between user practicality and digitization fidelity.  My research aims to break this trend, developing sensing systems that increase user digitization fidelity to create new and powerful computing experiences while retaining or even improving user practicality and accessibility, allowing such technologies to have a societal impact. Armed with such knowledge, our future devices could offer longitudinal health tracking, more productive work environments, full-body avatars in extended reality, and embodied telepresence experiences, to name just a few domains. </p

TouchPose: Hand Pose Prediction, Depth Estimation, and Touch Classification from Capacitive Images

Today's touchscreen devices commonly detect the coordinates of user input through capacitive sensing. Yet, these coordinates are the mere 2D manifestations of the more complex 3D configuration of the whole hand - a sensation that touchscreen devices so far remain oblivious to. In this work, we introduce the problem of reconstructing a 3D hand skeleton from capacitive images, which encode the sparse observations captured by touch sensors. These low-resolution images represent intensity mappings that are proportional to the distance to the user's fingers and hands. We present the first dataset of capacitive images with corresponding depth maps and 3D hand pose coordinates, comprising 65,374 aligned records from 10 participants. We introduce our supervised method TouchPose, which learns a 3D hand model and a corresponding depth map using a cross-modal trained embedding from capacitive images in our dataset. We quantitatively evaluate TouchPose's accuracy in touch classification, depth estimation, and 3D joint reconstruction, showing that our model generalizes to hand poses it has never seen during training and can infer joints that lie outside the touch sensor's volume. Enabled by TouchPose, we demonstrate a series of interactive apps and novel interactions on multitouch devices. These applications show TouchPose's versatile capability to serve as a general-purpose model, operating independent of use-case, and establishing 3D hand pose as an integral part of the input dictionary for application designers and developers. We also release our dataset, code, and model to enable future work in this domain

Endogenous auxin level is a critical determinant for in vitro adventitious shoot regeneration in potato (Solanum tuberosum L.)

Endogenous levels of indole-3-acetic acid (IAA) were determined in the internodal explants of Indian tetraploid potato cultivars (cvs) viz., Kufri Sutlej (K.Sutlej) and Kufri Giriraj (K.Giriraj). Seven fold higher level of endogenous IAA was recorded for cv K.Sutlej over cv K. Giriraj. As a result, perhaps there was a callusing response from the cut end of the internodal explants of both the cvs in the MS basal medium. The extent of callusing was relatively higher in cv K.Sutlej when compared to that in K.Giriraj. The callusing response was inhibitory to shoot morphogenesis. Inclusion of an established anti-auxin, 2,3,5-tri-iodobenzoic acid (TIBA) in the regeneration medium facilitated a high frequency adventitious shoot regeneration response with lower cytokinin levels. Murashige and Skoog (MS) medium containing TIBA at 2.5 mg l−1 and 0.25 mg l−1 zeatin evoked a 100% regeneration response (4.5 shoot buds per explant) in cv K.Sutlej within 20–25 days. However, in cv K.Giriraj, which had lower levels of endogenous IAA, 80% regeneration response (1.4 shoot buds per explant) was recorded in an extended period of 40–45 days on a medium containing 0.5 mg l−1 TIBA and 0.1 mg l−1 zeatin. Although, TIBA and zeatin induced shoot bud formation, it failed to support sustained growth of the regenerated shoots in cv K.Giriraj. Hence, 0.01 mg l−1 α-naphthaleneacetic acid (NAA) with a relatively higher concentration of zeatin (1.0 mg l−1) were used for sustained shoot regeneration (3.3 shoot buds per explant) within 25 days. From our results, it is evident that there was a difference in the requirement of exogenous zeatin levels required to induce a regeneration response in two cultivars of potato and this is attributed to the variable levels of endogenous IAA

Endogenous auxin level is a critial deterninant for in vitro adventitious shoot regeneration in potato(Solanum tuberosum L.)

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