José Chilo

Dr. José Chilo

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Academic Career Length

20Years (2007-Present)

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

Representative Publications

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30 June 2008 in Neurocomputing
Verified
Journal Article
Closed access
HBHenrik Berg
Henrik Berg
RORoland Olsson
Roland Olsson
TLThomas Lindblad
Thomas Lindblad
JCJosé Chilo
José Chilo
6 December 2024 in Machines
Verified
Journal Article
Open access
PDF file
TSTom Salm
Tom Salm
Kourosh TatarKourosh Tatar
Kourosh Tatar
JCJosé Chilo
José Chilo
This study presents a sound-based tool-wear monitoring system designed to overcome the limitations of conventional methods that focus solely on gradual and predictable wear patterns. The proposed system employs low-cost, high-frequency microphones and advanced signal processing—featuring analog/digital filtering, oversampling, signal conditioning, PLL-based synchronization, and feature extraction (ZCR, RMS)—to capture acoustic emissions during machining. Key innovations include optimized microphone placement, a custom PCB, and real-time data transfer via WiFi to MATLAB for analysis. Using the TreeBagger machine-learning algorithm, the system accurately predicts tool wear, detecting both gradual and abrupt wear patterns. Tested on EN 1.4307 (AISI/ASTM 304L) stainless steel, the system demonstrated robust performance in real-time tool-condition assessment. Its scalable and cost-effective design allows for the integration of additional sensors and features, providing a non-invasive and adaptive solution to enhance machining efficiency and reduce operational costs.
23 July 2024 in Sensors
Verified
Journal Article
Open access
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Rabé AnderssonRabé Andersson
Rabé Andersson
JGJavier Bermejo García
Javier Bermejo García
RARafael Agujetas
Rafael Agujetas
MCMikael Cronhjort
Mikael Cronhjort
JCJosé Chilo
José Chilo
Gait monitoring using hip joint angles offers a promising approach for person identification, leveraging the capabilities of smartphone inertial measurement units (IMUs). This study investigates the use of smartphone IMUs to extract hip joint angles for distinguishing individuals based on their gait patterns. The data were collected from 10 healthy subjects (8 males, 2 females) walking on a treadmill at 4 km/h for 10 min. A sensor fusion technique that combined accelerometer, gyroscope, and magnetometer data was used to derive meaningful hip joint angles. We employed various machine learning algorithms within the WEKA environment to classify subjects based on their hip joint pattern and achieved a classification accuracy of 88.9%. Our findings demonstrate the feasibility of using hip joint angles for person identification, providing a baseline for future research in gait analysis for biometric applications. This work underscores the potential of smartphone-based gait analysis in personal identification systems.
24 July 2015 in Wireless Personal Communications
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Journal Article
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JFJavier Ferrer-Coll
Javier Ferrer-Coll
SSSlimane Ben Slimane
Slimane Ben Slimane
JCJosé Chilo
José Chilo
PSPeter Stenumgaard
Peter Stenumgaard
7 June 2021 in IEEE Transactions on Nuclear Science
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Journal Article
Closed access
AAA. Argume
A. Argume
RCR. Coaguila
R. Coaguila
PYPablo Raul Yanyachi
Pablo Raul Yanyachi
JCJosé Chilo
José Chilo
In recent years, irrigations have been built on dry areas in Majes-Arequipa. Over time, the irrigations water forms moist areas in lower areas, which can have positive or negative consequences. Therefore, it is important to know in advance where the water from the new irrigation will appear. The limited availability of real-time satellite image data is still a hindrance to some applications. Data from environmental satellites NOAA (National Oceanic and Atmospheric Administration) are available fee and license free. In order to receive data, users must obtain necessary equipment. In this work we present a satellite data acquisition system with an RTL SDR receiver, two 137-138 Mhz designed antennas, Orbitron, SDRSharp, WXTolmag and MatLab software. We have designed two antennas, a Turnstile Crossed dipole antenna with Balun and a quadrifilar helicoidal antenna. The antennas parameter measurements show very good correspondence with those obtained by simulation. The RTL SDR RTL2832U receiver, combined with our antennas and software, forms the system for recording, decoding, editing and displaying Automatic Picture Transmission (APT) signals. The results show that the satellite image receptions are sufficiently clear and descriptive for further analysis.
22 October 2024 in Machines
Verified
Journal Article
Open access
PDF file
Rabé AnderssonRabé Andersson
Rabé Andersson
MCMikael Cronhjort
Mikael Cronhjort
JCJosé Chilo
José Chilo
The demand for remote rehabilitation is increasing, opening up convenient and effective home-based therapy for the sick and elderly. In this study, we use AnyBody simulations to analyze muscle activity and determine key parameters for designing a rehabilitation exoskeleton, as well as selecting the appropriate motor torque to assist patients during rehabilitation sessions. The exoskeleton was designed with a PID control mechanism for the precise management of motor positions and joint torques, and it operates in both automated and teleoperation modes. Hip and knee movements are monitored via smartphone-based IMU sensors, enabling real-time feedback. Bluetooth communication ensures seamless control during various training scenarios. Our study demonstrates that remotely controlled rehabilitation systems can be implemented effectively, offering vital support not only during global health crises such as pandemics but also in improving the accessibility of rehabilitation services in remote or underserved areas. This approach has the potential to transform the way physical therapy can be delivered, making it more accessible and adaptable to the needs of a larger patient population.