Quality control engineering for software screening related to motor neuron disease EMG biomarkers used in clinical practice, at Natus Medical Incorporated
: internship

  • Marta Isabel Soares dos Santos (Student)

Student thesis: Master's Thesis


As part of a growing biomedical engineer, fieldwork and hands-on activities are great pillars for professional development and improved knowledge. The internship at Natus Medical allowed integration with many enterprise tools in a real environment, especially through online remote approaches, and contact with the technical specifications of system hardware and software algorithms. Throughout the months, there was the possibility to work with international teams with global experience in the EMG field and acquire knowledge from many key opinion leaders for clinical EMG approaches and great technology attributes. The EMG algorithms integrated into Natus’s software are a great tool for disease progression tracking and are used as biomarkers in patients with Amyotrophic Lateral Sclerosis and other Neuromuscular Disorders. First, knowledge of EMG processes and procedures was fundamental, as well as the physiology behind the recorded waveforms for healthy and neuropathic motor units. Participating as a quality control engineer student in the team, the main purpose was to be critical regarding the implemented methodologies, namely Motor Unit Number Estimation and Motor Unit Number Index. By doing the comparison between those methods, the conclusion is that the application of MUNIX, present in the software Natus Elite’s current version, is the elected methodology, as it is an index rather than an estimation, which can have interpretation issues. Additionally, it has a faster recording time, and it is able to analyze larger muscles, being more comprehensive than MUNE computed techniques present into the same software. However, it has limitations, such as the need of the subject’s cooperation, which can be overtake using CMAP Scan. That being said, the symbiotic use of both techniques for motor unit degeneration monitoring is the best approach to provide reliable results and better outcomes for patients suffering from such progressive and disabling conditions.
Date of Award17 Jul 2023
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorPedro Miguel Rodrigues (Supervisor) & Simone Poggi (Co-Supervisor)


  • Electromyography (EMG)
  • Amyotrophic lateral sclerosis (ALS)
  • Neuromuscular disorder (NMD)
  • MUNE (motor unit number estimation)
  • Motor unit number index (MUNIX)


  • Mestrado em Engenharia Biomédica

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