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Background and aims
Uncertainty persists over the effects of blood pressure (BP) lowering in acute stroke. The INTEnsive ambulance-delivered blood pressure Reduction in hyper-Acute stroke Trial (INTERACT4) aims to determine efficacy and safety of hyperacute intensive BP lowering in patients with suspected acute stroke. Given concerns over the safety of this treatment in the pre-hospital setting, particularly in relation to patients with intracerebral hemorrhage, we provide an update on progress of the study and profile of participants to date.

Methods
INTERACT4 is an ongoing multicentre, ambulance-delivered, randomized, open-label, blinded endpoint trial of pre-hospital BP lowering in patients with suspected acute stroke and elevated BP in China. Patients are randomized via a mobile phone digital system to intensive (target systolic BP [SBP] <140mmHg within 30 min) or guideline-recommended BP …

Visible light positioning (VLP) based on the received signal strength (RSS) can leverage a dense deployment of LEDs in future lighting infrastructure to provide accurate and energy-efficient indoor positioning. However, its positioning accuracy heavily depends on the density of collected fingerprints, which is labor-intensive. In this work, we propose a data pre-processing method, including data cleaning and data augmentation, to construct reliable and dense fingerprint samples, thereby alleviating the impact of noisy samples as well as reducing labor intensity. Extensive experiments demonstrate that our proposed method achieves an average positioning error of 1.7 cm, utilizing a sparse dataset that reduces the fingerprint collection effort by 98 percent. Running a tinyML-based model for VLP on the Arduino Nano microcontroller, we also show the possibilities for deploying RSS fingerprint-based VLP systems on …

Stroke is the second leading cause of death worldwide. The burden of disability after a stroke is also large, and is increasing at a faster pace in low-income and middle-income countries than in high-income countries. Alarmingly, the incidence of stroke is increasing in young and middle-aged people (ie, age< 55 years) globally. Should these trends continue, Sustainable Development Goal 3.4 (reducing the burden of stroke as part of the general target to reduce the burden of non-communicable diseases by a third by 2030) will not be met.

Contact-free interaction with public devices could become popular. To achieve this purpose, state-of-the-art methods mainly use cameras to capture mid-air hand gestures, which are power-hungry and can raise privacy issues. In this work, we design LightDigit, a system for fingertip air-writing of digits with ambient light and photodiodes, to enable contact-free interactions with public devices. The key enabler is detecting and interpreting dynamic shadows on photodiodes introduced by fingertip movements. We design an embedded deep learning model LightConvRNN –customized ConvRNN with attention pooling– to capture spatial and temporal patterns in the dynamic shadows. We evaluate LightDigit through extensive experiments under different light conditions. Evaluation results show that our model can achieve an accuracy of up to 98%. Through model compression, the model size is reduced by 92% with less …