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Personal profile

Personal Statement

My PhD on Biomedical Engineering involved understanding the muscle activity from the forearm, identifying the surface electromyographic patterns involved and correlating them with specific hand movements leading to improvements in the control of a myoelectric driven prosthesis, specifically of the thumb.

I have experience in real-time electrophysiological data acquisition, time-domain analyses (i.e. amplitude signal analysis, RMS, statistical analyses), time-frequency domain analyses (i.e. coherence estimates and cumulant analysis), machine learning (i.e. SOFMs, PCA), developing research protocols, health statistics, patent writing and application, CPD development.

My career development has allowed me to develop expertise in MATLAB programming, ethical research, upper limb anatomy and biomechanics, medical devices commercialisation, risk analysis and medical device certification.

I am committed to teaching, research, knowledge exchange and development, aiming to respond to the growing demand for health services by training capable professionals and to improve the quality of life in patients that have suffered the loss of function, sensation or the limb(s), resulting in a serious and challenging life-changing event in these patient populations.

My research vision is to assist vulnerable patient populations with the opportunity to self-manage their own health, by developing, evaluating and commercialising new medical and assistive technologies.

Research Interests

I am particularly interested in the use of high-density electromyography (EMG) and its analysis applied to rehabilitation, gaming, prevention, and furthering in the understanding of other interventions using EMG as a quantitative outcome measure. 


Expertise & Capabilities

* Acquisition, processing and analysis of high density surface electromyography

* Analysis of muscle fatigue and neural drives

* Development of medical technology for orthotics, prosthetics and other rehabilitation devices

* Commercialising of medical devices

* Intellectual Property

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2017 2019

Research Output 2013 2018

An algorithm to identify and quantify intermittent (burst-like) muscular patterns of activity in HD-sEMG signals

Aranceta-Garza, A. & Merletti, R., 30 Jun 2018, International Society of Electrophysiology and Kinesiology: Abstracts, Presentations. Dublin, p. 205-205 1 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Extraction of information from high-density EMG: recent development and perspectives.

Merletti, R., Aranceta Garza, A., Afhsaripour, B. & Soedirdjo, S., 2018.

Research output: Contribution to conferenceKeynote



Activities 2018 2018

  • 1 Participation in workshop, seminar, course

Frontiers of Engineering for Development: Royal Academy of Engineering

Alejandra Aranceta Garza (Participant)
30 Oct 20182 Nov 2018

Activity: Participating in or organising an event typesParticipation in workshop, seminar, course