Learning to Estimate Critical Gait Parameters from Single-View RGB Videos with Transformer-Based Attention Network

Musculoskeletal diseases and cognitive impairments in patients lead to difficulties in movement as well as negative effects on their psychological health. Clinical gait analysis, a vital tool for early diagnosis and treatment, traditionally relies on expensive optical motion capture systems. Recent advances in computer vision and deep learning have opened the door to more accessible and cost-effective alternatives. This paper introduces a novel spatio-temporal Transformer network to estimate critical gait parameters from RGB videos captured by a single-view camera. Empirical evaluations on a public dataset of cerebral palsy patients indicate that the proposed framework surpasses current state-of-the-art approaches and show significant improvements in predicting general gait parameters (including Walking Speed, Gait Deviation Index - GDI, and Knee Flexion Angle at Maximum Extension), while utilizing fewer parameters and alleviating the need for manual feature extraction.Comment: Accepted at ISBI 2024 (21st IEEE International Symposium on Biomedical Imaging

Participatory agro-climate information services: A key component in climate resilient agriculture

The brief promotes participatory agro-climate information services as a key component in achieving climate-smart agriculture. The brief emphasizes that actionable agro-climate information starts with—and responds to—gender-based needs of farmers, integrated at all stages of the value chain. Timely forecasts and accurate agroclimate advisories have been proven to provide farmers with production, adaptation, and mitigation benefits

Telehealth technology: Potentials, challenges and research directions for developing countries

Telehealth has been developed and successfully applied in clinical practices, gained a strong interest and demonstrated its usefulness for medical diagnosis, treatments and rehabilitation worldwide. The advent of high speed communication technology and complex signal processing techniques, and recent advancements in cloud and cognitive computing, has created a new wave of opportunities for delivering remote healthcare applications and services, where the cost-effective diagnosis and treatment solutions as well as healthcare services are important and need to be deployed widely. Nevertheless, there is still a significant challenge in fully adopting this technology due to asymmetry among the healthcare centers, hospitals and the user-ends, especially in developing countries. This paper provides an overview of the telehealth, then to addresses the possible telehealth technologies and applications that could be applied to improve the healthcare service performance, with the focus on the developing countries. The incorporation of different technologies in telehealth including, Internet of Things (IoT), cloud and cognitive computing, medical image processing and effective encoding is introduced and discussed. Finally, the possible research directions, challenges for the efficient telehealth, and potential research and technology collaborations are outlined

Joint UAV Placement and IRS Phase Shift Optimization in Downlink Networks

This study investigates the integration of an intelligent reflecting surface (IRS) into an unmanned aerial vehicle (UAV) platform to utilize the advantages of these leading technologies for sixth-generation communications, e.g., improved spectral and energy efficiency, extended network coverage, and flexible deployment. In particular, we investigate a downlink IRS-UAV system, wherein single-antenna ground users (UEs) are served by a multi-antenna base station (BS). To assist the communication between UEs and the BS, an IRS mounted on a UAV is deployed, in which the direct links are obstructed owing to the complex urban channel characteristics. The beamforming at the BS, phase shift at the IRS, and the 3D placement of the UAV are jointly optimized to maximize the sum rate. Because the optimization variables, particularly the beamforming and IRS phase shift, are highly coupled with each other, the optimization problem is naturally non-convex. To effectively solve the formulated problem, we propose an iterative algorithm that employs block coordinate descent and inner approximation methods. Numerical results demonstrate the effectiveness of our proposed approach for a UAV-mounted IRS system on the sum rate performance over the state-of-the-art technology using the terrestrial counterpart

Dimethyl 2-[22,24-dimethyl-23-oxo-8,11,14-trioxa-25-aza­tetra­cyclo­[19.3.1.02,7.015,20]penta­cosa-2,4,6,15(20),16,18-hexaen-25-yl]but-2-enedioate

The title compound, C29H33NO8, is a product of the Michael addition of the cyclic secondary amine subunit of the aza-14-crown-4 ether to dimethyl acetyl­enedicarboxyl­ate. The piperidinone ring exhibits a distorted chair conformation, and the dimethyl ethylenedicarboxylate fragment has a cis configuration with a dihedral angle of 78.96 (5)° between the two carboxyl­ate groups. The crystal packing is stabilized by weak C—H⋯O hydrogen bonds