R&D Projects and Clinical Studies

R&D Projects



Project No.: INNEST/2021/348

Project funded by the Agència Valenciana de la Innovació (AVI)

Game-changing value proposition for early diagnosis and effective intervention of sarcopenia syndrome: the progressive loss of skeletal muscle that comes with aging

iSARC-Genetics project born with the mission of providing a novel and cost-efficient scientific and technological solution in the field of health, and with a value proposition for the prevention and control of sarcopenia, through the development of decision support system for the  diagnosis and monitoring of Sarcopenia, based on a new wearable imaging device (wearable ultrasound), integrated into an innovative cloud computing system grounded on Artificial Intelligence (AI) that will allow early detection of this prevalent muscle disease, and the remote monitoring of patients in their personalized treatment and care



Project No.: 2021/C005/00150950

Project funded by Ministerio de Asuntos Economicos y Transformación Digital (RED.ES)

2D and 3D Convolutional Neural Networks to train Deep Learning Models for the advance analysis of ultrasound images

Objective: The technological solution defined in the framework of the iRIA project aims to investigate an innovative computational system based on Deep Learning Models for advanced analysis of US images, in order to improve and optimize the automation of relevant image features, using Deep Neural Networks (DNNs).

Expected results:

New automated ultrasound image biomarker extraction system.

Implementation of an AI model for ultrasound image analysis.

Generation of structured reports

Clinical Studies


iSARC Investigation

SERGAS Reg. Code: 2022/326

iSARC™ Research Project. Early diagnosis of sarcopenia

through Ecographic images processed and analyzed by the PIIXMED™ system (Cloud Web Application Medical Device as a Computer Program)

Hypothesis of the iSARC Study: A tool such as PIIXMED™ could simplify the diagnosis of sarcopenia, reliably confirming muscle quantity and quality, helping the medical professional to diagnose through sarcopenia indexes and being easy to handle in Primary Care and hospitals.

Objectives: The aim of the iSARC™ research study is to analyze the variation of ultrasound parameters of muscle architecture with age in a healthy population. To identify "ranges of normality" in ultrasound parameters of muscle architecture by age and sex groups. To identify patients with sarcopenia with ultrasound study. To determine cut-off points to establish sarcopenia indexes. To evaluate the PIIXMED™ system as a valid, consistent and reproducible diagnostic tool for the finding of sarcopenia.


WUS System

Project No.: SNEO-20211084

Project funded by Centro para el Desarrollo Tecnológico y la Innovación (CDTI)

Supported by the  Ministerio de Ciencia e Innovación.

Project funded by Unión Europea –Next Generation EU. 

Intelligent biomedical imaging system for remote patient monitoring and quantitative image biomarker analysis of physiological parameters

Dawako Medtech through the WUS System project is developing an innovative patented multi-modal Wearable Ultrasound Apparatus system  for the acquisition of ultrasound images, bioelectrical signals (EMG, ECG) and spectrometry (NIRS) in motion, in patch format: WUS System, which together with the PIIXMED platform, as an intelligent system, in a Cloud environment, based on Artificial Intelligence (AI) and Machine Learning algorithms, allows the analysis  of quantitative biomarkers of ultrasound images and remote monitoring of patients, for personalized healthcare and the physiological performance of users and/or patients



Project No.: CPP2022-009718

Project funded by Ministerio de Ciencia e Innovación (MICINN)

Development of a Sarcopenia prediction model by Integrating Genome Analysis, Microbiome, and other Biochemical Biomarkers

SARCOTECH project get focus on development of a Sarcopenia prediction model by Integrating Genome Analysis, Microbiome, and other Biochemical Biomarkers. The proposal involves the combination of omics, Bioinformatics, and Information and Communication Technologies to develop a rapid and low-cost solution for the massive screening of sarcopenia. The novelty of the proposal consists in combining multiple risk factors on sarcopenia, such as genetics, microbiota, clinical biomarkers, and lifestyle parameters in a machine learning algorithm capable of predicting the onset and severity of this geriatric syndrome