This paper presents results of using a simple bit-serial architecture as a method of designing an extremely low-power and low-cost neural network processor for epilepsy seizure prediction. The proposed concept is based on a novel bit-serial data processing unit (DPU) which implements the functionality of a complete neuron and uses bit-serial arithmetic.
The objective of this study was to examine changes in applied force and rate of chest compression (CC) during 5 min of CC with a target CC rate of 90/min (CC90) or 120/min (CC120) with and without metronome guidance during simulated neonatal CPR.
This paper presents a new platform to monitor the arm and hand activity of stroke patients during rehabilitation exercises in hospital and at home during their daily living activities. The platform provides relevant data to the therapist in order to assess the patients physical state and adapt the rehabilitation program if necessary.
Bronchoscopy inspection, as a follow-up procedure next to the radiological imaging, plays a key role in the diagnosis and treatment design for lung disease patients. When performing bronchoscopy, doctors have to make a decision immediately whether to perform a biopsy.
In this paper, the design of a smart headband for epileptic seizure detection is presented. The proposed headband consists of four key components: 1) an analog front-end circuitry, 2) an epileptic seizure detection tag (ESDT), 3) a Bluetooth Low Power (BLE) chip, and 4) customized electrodes.
Accumulation of excess air and water in the lungs leads to breakdown of respiratory function and is a common cause of patient hospitalization. Compact and non-invasive methods to detect changes in lung fluid accumulation can allow physicians to assess patients’ respiratory conditions.
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