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My research focuses on the intersection of wearable sensing, human-centered design, and clinical translation.
By leveraging mechanical engineering principles and advanced signal processing, I develop diagnostic tools that bridge the gap between lab-based precision and real-world utility. From quantifying fetal health through IMU-based systems to optimizing how engineers make decisions in the field, my work is driven by a commitment to improving patient outcomes through robust, context-aware engineering solutions.
My research focuses on the intersection of wearable sensing, human-centered design, and clinical translation.
By leveraging mechanical engineering principles and advanced signal processing, I develop diagnostic tools that bridge the gap between lab-based precision and real-world utility. From quantifying fetal health through IMU-based systems to optimizing how engineers make decisions in the field, my work is driven by a commitment to improving patient outcomes through robust, context-aware engineering solutions.
Fetal Movement Monitoring
Utilizing wearable IMU-based systems and machine learning to enable continuous, non-invasive monitoring of fetal health outside of traditional clinical settings.
Technical Competencies:
Data Science & Machine Learning
Digital Signal Processing & Sensor Fusion
Research Design & Clinical Translation
Skills: MatLab, Python (PyTorch, TensorFlow, Scikit-Learn), R, Linux/Bash
Associated Publications:
Lucy Spicher, Carrie Bell, Kathleen H. Sienko, and Xun Huan. "Four Data-Driven Design Choices for IMU-Based Fetal Movement Detection: Sensitivity, Thresholding, Windowing, and Filtering." In 2026 Design of Medical Devices Conference (DMD26), 2026.
Lucy Spicher, Carrie Bell, Kathleen H. Sienko, and Xun Huan. "Comparative analysis of machine learning approaches for fetal movement detection with Linear acceleration and angular rate signals." Sensors 25, no. 9 (2025): 2944.
Lucy Spicher, Carrie Bell, Xun Huan, and Kathleen Sienko. "Exploring random forest machine learning for fetal movement detection using abdominal acceleration and angular rate data." In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1-4. IEEE, 2024.
Contextual Engineering
Investigating the cognitive processes of experienced engineers to understand how contextual factors—social, environmental, and economic—shape high-stakes design decisions.
Technical Competencies:
Design Research & Methodology
Human-Centered Design (HCD) Frameworks
Qualitative Data Synthesis & Analysis
Skills: Semi-structured interviewing, qualitative coding, thematic analysis, inter-coder reliability
Associated Publications:
Lucy Spicher, Lisa Kong, Jean Avaala, Amna Batool, Grace Burleson, Kentaro Toyama, and Kathleen H. Sienko. "Contextual Factors Incorporated by Experienced Design Practitioners: A Study Across Three Design Domains." Manuscript under review.
Jean Avaala, Grace Burleson, Lucy Spicher, Amna Batool, Kentaro Toyama, Kathleen H. Sienko, and Julia Kramer. "Exploring Contextual Factor Incorporation Across Design Phases: A Study of Medical Device and Consumer Product Designers in High and Low-Income Settings." Accepted for publication in 2026 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC-CIE), 2026.
Pathological Gait Classification
Applying biomechanical modeling and data-driven approaches to differentiate and classify movement disorders, facilitating more personalized rehabilitation strategies.
Technical Competencies:
Clinical Biomechanics & Gait Kinematics
Deep Learning & Time-Series Modeling
Skills: MatLab, Python (PyTorch, TensorFlow, Scikit-Learn)
Associated Publications:
Safa Jabri, Lucy Spicher, Wendy Carender, Jenna Wiens, and Kathleen H. Sienko. "Automatically Classifying Vestibular Gait Using Time-series Data from Wearable IMUs." In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1-4. IEEE, 2024.
3D Printed Solutions for Rural Healthcare
Implementing hyperlocal manufacturing and additive manufacturing (Kijenzi) to address supply chain gaps and meet urgent clinical needs in resource-constrained environments like rural Kenya.
Technical Competencies:
Reverse Engineering & Hardware Adaptation
Rapid Prototyping & Technical Validation
Design for Additive Manufacturing (DfAM)
Skills: CAD (SolidWorks, Autodesk Fusion 360), rapid prototyping, additive manufacturing, semi-structured interviewing
Associated Publications:
Lucy Spicher and John Gershenson. "Key Factors of Design: 3D Printed Occupational Therapy Products in Developing Communities." In 2020 IEEE Global Humanitarian Technology Conference (GHTC), pp. 1-7. IEEE, 2020.
Daniel Kats, Lucy Spicher, Ben Savonen, and John Gershenson. "Paper 3d printing to supplement rural healthcare supplies—what do healthcare facilities want?." In 2018 IEEE Global Humanitarian Technology Conference (GHTC), pp. 1-8. IEEE, 2018.
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