Masood Nevisipour
Lead Human Factors & Biomechanics Engineer @Seismic
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WORK HISTORY
Lead Human Factors & Biomechanics Engineer @Seismic
Menlo Park, CA, US
Human-centered design, testing, and validation of a soft wearable robotic exo-suit to support trunk, lower back, pelvis, and hips and enhance workers safety. Working with different groups (e.g, human factors, algorithm development, soft goods design, mechanical)- Development of IMU-based human motion classification & injury risk assessment algorithms- Led UX/UI design for a wearable robotic exosuit app and on-device interface.
EDUCATION
Arizona State University
Master of Science (M.Sc.), Mechanical Engineering
Sharif University of Technology
Bachelor of Science (B.Sc.), Mechanical Engineering
Arizona State University
Doctor of Philosophy - PhD, Mechanical Engineering
ABOUT MASOOD NEVISIPOUR
PhD in Mechanical Engineering with over 10 years of experience in:Human Biomechanics & Human Factors-• Design of Human Experiments: human-device interaction, human factors, usability, ergonomics, injury risk, fatigue, wearability, comfort, fit, gait, balance, and falls in 200+ human subjects • Human Factors & Ergonomics: Applied human factors, biomechanics, ergonomics, and 3D anthropometric principles/analysis as well as regulatory compliance (OSHA, NIOSH, FDA, ISO) to develop user-centered product requirements and validation test protocols for wearable devices. • UX/UI design: UX/UI design requirements for a wearable device app & UI board, task and use-related error analysis, summative & formative usability testing, users\' data collection & analysis.• Motion Capture: Marker, IMU, video-based data collection/analysis in Vicon Nexus, OpenSim, Python, Visual 3D, Cortex, MATLAB.• Motion classification algorithm development: Developed real-time algorithms in Python and MATLAB for classifying human activity (e.g, standing, walking, stooping, squatting, sitting) using IMU data from a soft exosuit.• Injury risk assessment algorithm development: Developed an algorithm that detects awkward postures and outputs a risk score for lower back injury.Robotics-• Hands-On Experience: Designed and built soft wearable robots to support trunk, lower back, and hips.• Experimental Validation: Evaluated wearable robots’ performance, impact on biomechanical metrics, comfort, usability, safety, and regulatory compliance.• Control System Design: PID, Lead/Lag, PLC, LQR using MATLAB, MATLAB Simulink, and LabView • Sensors: IMU, Accelerometer, gyroscope, EMG, IR, load cell• Trajectory planning: KUKA, SCARA, line tracking car robotData Analysis-• Statistics: Generalized Mixed-effects Models, regression, LDA, PCA, Pearson’s correlation, ANOVA, MANOVA, ANCOVA, MANCOVA, chi-square, power analysis, sample size, probability distributions, data visualization; using Python, R, MATLAB, SPSS, SAS, Tableau• Signal Processing: Digital filtering, IMU, EMG analysis, force plate.• Machine Learning: Classification, clustering, linear regressionDesign-• Biomedical Device Design: Fall-risk assessment phone application using C++, robotic gripper end effector using SolidWorks• CAD, CAM, CAE, FEA: SolidWorks, CATIA, AutoCAD, ANSYS
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