Miguel Neto

Mr. Miguel Neto


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 September 2020 in Sensors
Verified
Journal Article
Open access
PDF file
PRPedro Ribeiro
Pedro Ribeiro
ASANA SOARES
ANA SOARES
RGRafael Girão
Rafael Girão
MNMiguel Neto
Miguel Neto
Susana Cardoso De FreitasSusana Cardoso De Freitas
Susana Cardoso De Freitas
Back and spine-related issues are frequent maladies that most people have or will experience during their lifetime. A common and sensible observation that can be made is regarding the posture of an individual. We present a new approach that combines accelerometer, gyroscope, and magnetometer sensor data in combination with permanent magnets assembled as a wearable device capable of real-time spine posture monitoring. An independent calibration of the device is required for each user. The sensor data is processed by a probabilistic classification algorithm that compares the real-time data with the calibration result, verifying whether the data point lies within regions of confidence defined by a computed threshold. An incorrect posture classification is considered if both accelerometer and magnetometer classify the posture as incorrect. A pilot trial was performed in a single adult test subject. The combination of the magnets and magnetometer greatly improved the posture classification accuracy (89%) over the accuracy obtained when only accelerometer data were used (47%). The validation of this method was based on image analysis.

28 July 2021 in Sensors
Verified
Journal Article
Open access
PDF file
MNMiguel Neto
Miguel Neto
PRPedro Ribeiro
Pedro Ribeiro
RNRicardo Nunes
Ricardo Nunes
LJLorenzo Jamone
Lorenzo Jamone
Alexandre BernardinoAlexandre Bernardino
Alexandre Bernardino
Susana Cardoso De FreitasSusana Cardoso De Freitas
Susana Cardoso De Freitas
Tactile sensing is crucial for robots to manipulate objects successfully. However, integrating tactile sensors into robotic hands is still challenging, mainly due to the need to cover small multi-curved surfaces with several components that must be miniaturized. In this paper, we report the design of a novel magnetic-based tactile sensor to be integrated into the robotic hand of the humanoid robot Vizzy. We designed and fabricated a flexible 4 × 2 matrix of Si chips of magnetoresistive spin valve sensors that, coupled with a single small magnet, can measure contact forces from 0.1 to 5 N on multiple locations over the surface of a robotic fingertip; this design is innovative with respect to previous works in the literature, and it is made possible by careful engineering and miniaturization of the custom-made electronic components that we employ. In addition, we characterize the behavior of the sensor through a COMSOL simulation, which can be used to generate optimized designs for sensors with different geometries.