2008―2012, Mechanical Engineering，Stanford University, Ph.D.
2005―2008, Mechanical Engineering，Stanford University, M.S.
2000―2005, Mechanical Engineering and Computer Engineering，LeTourneau University, B.S.

2022-present Professor, School of Mechanical Engineering，Shanghai Jiao Tong University, Shanghai, China
2016-2021 Associate Professor, School of Mechanical Engineering，Shanghai Jiao Tong University, Shanghai, China
2013-2015 Assistant Professor, School of Mechanical Engineering，Shanghai Jiao Tong University, Shanghai, China
2012-2013 Postdoctoral Research Fellow, Department of Bioengineering，Stanford University, Stanford, California, USA

2018 Imperial College, Visiting Scholar
2017 Stanford University, Visiting Scholar
2011 Tsinghua University, Visiting Scholar

Wearable sensing and feedback systems, Sensor fusion algorithms, Artificial Intelligence, Human movement retraining

1. Title: Intelligent Somatosensory System for Embodied Multimodal Interaction
Role: PI
Dates: 2025.01.01 – 2027.12.31
Source: National Natural Science Foundation of China – International Collaboration Fund for
Creative Research Teams

2. Title: Collaborative Project on Innovative Interaction Technologies for Multi-modal Data-Based
Human Motion Perception and AI-Powered Coaching
Role: PI
Dates: 2025.08.13 – 2026.8.12
Source: Huawei Research

3. Title: Automated Wearable Knee Osteoarthritis Detection and Assessment Based on BST
Sensors
Role: PI
Dates: 2024.08.26 – 2025.12.31
Source: Bosch Sensortec

4. Title: Basic Functionality of Golf Measurement for Smart Wearable Sensors on the Hand and
Waist
Role: PI
Dates: 2024.05.14 – 2025.5.13
Source: Sculpted Earth

5. Title: Wearable Soft Acoustic Waveguides for Hand Gesture Recognition in Daily
Activities
Role: PI
Dates: 2023.01.01 – 2024.12.31
Source: National Natural Science Foundation of China – Major Project: RFIS-II

6. Title: Soft Axial and Shear Force Sensing Wearable Wristband Based on 3D Hall Effect Sensor
Matrices for Human Computer Interaction
Role: PI
Dates: 2023.09.01 – 2024.08.31
Source: ByteDance

7. Title: Intelligent Step Counting for Smart Wearable Devices
Role: PI
Dates: 2024.01.08 – 2025.01.07
Source: Love and Protect Technology Company

8. Title: Wearable Algorithms for Musculoskeletal Rehabilitation
Role: PI
Dates: 2022.09.26 – 2024.01.17
Source: TensorHealth

9. Title: Multi-IMU Fusion for Whole Body Movement Detection
Role: PI
Dates: 2021.08.31 – 2023.03.30
Source: Huawei Research

10. Title: Research on Gait Retraining via Wearable Body Sensing Networks after Total Knee
Arthroplasty
Role: PI
Dates: 2019.01.01 – 2022.12.31
Source: National Natural Science Foundation of China – Major Project

11. Title: Exploring Wearable Solutions for Functional Evaluation and Motor Rehabilitation in Stroke
Patients
Role: PI
Dates: 2018.11.27 – 2022.11.26
Source: Xsens Technologies

12. Title: Research on Multi-sensor Fusion Wearable Hand Gesture Recognition for Automatic Sign
Language Detection
Role: PI
Dates: 2020.01.01 – 2021.12.31
Source: National Natural Science Foundation of China – RFIS-I

13. Title: Development of a Lower Limb Assistive Soft Exoskeleton
Role: co-PI
Dates: 2018.04.30 – 2021.06.30
Source: Science and Technology Commission of Shanghai Municipality

14. Title: Kids Activity Recognition Algorithm Based on BST Sensors and Transfer Learning
Role: PI
Dates: 2020.06.30 – 2020.12.20
Source: Bosch Sensortec

15. Title: Hand Gesture Recognition via Wrist-worn Muscle Force Sensing
Role: PI
Dates: 2019.09.01 – 2020.04.30
Source: Huawei Research

16. Title: Kinematics Analysis and Force Position Control Synthesis of Continuum Robots for Deep
Cavity Operation
Role: co-PI
Dates: 2015.01.01 – 2019.12.31
Source: National Natural Science Foundation of China – Key Project

17. Title: Human Running Posture and Load Estimation via Wearable Sensors
Role: PI
Dates: 2019.05.01 – 2019.10.31
Source: Huawei Research

18. Title: Research on a Wearable Sensing and Haptic Feedback Gait Retraining System to Improve
Knee Osteoarthritis
Role: PI
Dates: 2016.01.01 – 2018.12.31
Source: National Natural Science Foundation of China – Youth Science Foundation

19. Title: Research on Human Energy Harvesting through Gait Retraining and Regenerative, Smart
Shoe Design
Role: PI
Dates: 2017.01.01 – 2018.12.31
Source: National Natural Science Foundation of China – RFIS-I

20. Title: Machine Learning to Classify Rider Ability and Riding Conditions on Dockless Shared Bikes
Role: PI
Dates: 2018.07.01 – 2018.12.31
Source: Bosch Sensortec

21. Title: Wearable Sensing and Haptic Feedback for Knee Osteoarthritis
Role: PI
Dates: 2016.01.01 – 2018.12.31
Source: Shanghai Jiao Tong University – Foreign Professor Research Initiative

22. Title: Soft Robotics Movement Sensing and Feedback for Preventing Falls in Older Adults
Role: PI
Dates: 2014.09.01 – 2017.08.31
Source: University of Michigan – Shanghai Jiao Tong University Collaboration Research Fund

23. Title: A Wearable Sensing and Haptic Feedback System for Movement Training and Assessment
Role: PI
Dates: 2014.07.01 – 2017.06.30
Source: Science and Technology Commission of Shanghai Municipality (Yangfan Program)

24. Title: Smart Shoe Development for Interactive Exercising Games
Role: PI
Dates: 2015.06.01 – 2016.12.01
Source: Danyang Chenhui Mechatronics Company

25. Title: Wearable Sensing and Haptic Feedback System for Human Movement Training and
Assessment
Role: PI
Dates: 2014.01.01 – 2016.06.30
Source: China 985 Program at SJTU

26. Title: Bio-Signal Based Hand and Finger Action Perception (Hand-Gesture Recognizing
Wristband)
Role: PI
Dates: 2015.05.01 – 2016.06.01
Source: Samsung Communications Technology Research & Development Center

Journal Articles
1. Sabaty A, Fishman A, Batcir S, Tan T, Shull PB, Levy K, Fischer AG, “Novel deep learning model to estimate knee flexion and adduction moments with wearable IMUs during treadmill and overground walking,” IEEE Journal of Biomedical and Health Informatics, In press, 2025.
2. Li D, Chen C, Zhu K, Guo R, Shull PB, “Integrating motor unit activity with deep learning for real-time, simultaneous and proportional wrist angle and grasp force estimation,” IEEE Transactions on Biomedical Engineering, In press, 2025.
3. Li Z, Lin Y, Shull PB, Ren H, “Disentangling contact location for stretchable tactile sensors from soft waveguide ultrasonic scatter signals, Advanced Intelligent Systems, 7(5):2400561, 2025.
4. Wang H, Ullah Z, Gazit E, Brozgol M, Hausdorff JM, Shull PB, Penina P, “Step width haptic feedback for gait stability in spinocerebellar ataxia: Preliminary results,” Movement Disorders, 40(4): 745-751, 2025.
5. Fan B, Zhang L, Cai S, Du M, Liu T, Li Q, Shull PB, “Influence of sampling rate on wearable IMU orientation estimation accuracy for human movement analysis,” Sensors, 25(7): 1976, 2025.
6. Pan H, Li D, Chen C, Shull PB, “High-density EMG grip force estimation during muscle fatigue via domain adaptation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 33: 925-934, 2025.
7. Li J, Kang P, Shull PB, “Multi-target unsupervised transfer learning improves wearable-sensor cross-body-position activity recognition via inter-target shared representation,” IEEE Sensors Journal, 25(5): 9101-9112, 2025.
8. Sun T, Tan T, Li D, Markert B, Shull PB, Bamer F, “Influence of number of subjects and number of trials on biomechanical variable estimation via deep-learning models and wearable IMUs during drop landings,” IEEE Sensors Journal, 25(4): 7532-7543, 2025.
9. Wang H, Ullah Z, Gazit E, Brozgol M, Tan T, Hausdorff JM, Shull PB, Ponger P, “Step width estimation in individuals with and without neurodegenerative disease via a novel data-augmentation deep learning model and minimal wearable inertial sensors,” IEEE Journal of Biomedical and Health Informatics, 29(1): 81-94, 2025.
10. Zhu K, Li D, Li J, Shull PB, “Real-time IMU-based kinematics in the presence of wireless data drop,” IEEE Journal of Biomedical and Health Informatics, 28(11): 6512-6524, 2024.
11. Alemu MY, Lin Y, Shull PB, “EchoGest: Soft ultrasonic waveguides based sensing skin for subject-independent hand gesture recognition,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32:2366-2375, 2024.
12. Lin J, Gregg RD, Shull PB, “Improving task-agnostic energy shaping control of powered exoskeletons with task/gait classification,” IEEE Robotics and Automation Letters, 9(8): 6848-6855, 2024.
13. Lin Y, Alemu MY, Shi B, Nanayakkara T, Shull PB, “Influence of soft materials on ultrasonic waveguide signal quality for wearable human motion detection across the legs, arms, and face,” IEEE Transactions on Instrumentation and Measurement, 73: 9511415, 2024.
14. Sarwat H, Alkhashab A, Song X, Jiang S, Jia J, Shull PB, “Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks,” Journal of NeuroEngineering and Rehabilitation, 21(1): 100, 2024.
15. Pan H, Wang H, Li D, Zhu K, Gao Y, Yin R, Shull PB, “Automated, IMU-based spine angle estimation and IMU location identification for telerehabilitation,” Journal of NeuroEngineering and Rehabilitation, 21(1):96, 2024.
16. Yang X, Xu Z, Liu H, Shull PB, Redmond S, Liu G, Wang C, “A multiscale cross-modal interactive fusion network for human activity recognition using wearable sensors and smartphones,” IEEE Internet of Things Journal, 11(16): 27139-27152, 2024.
17. Li D, Kang P, Yu Y, Shull PB, “Graph-driven simultaneous and proportional estimation of wrist angle and grasp force via high-density EMG,” IEEE Journal of Biomedical and Health Informatics, 28(5): 2723-2732, 2024.
18. Tan T, Shull PB, Hick JL, Uhlrich SD, Chaudhari AS, “Self-supervised learning improves accuracy and data efficiency for IMU-based ground reaction force estimation,” IEEE Transactions on Biomedical Engineering, 71(7): 2095-2104, 2024.
19. Lin Y, Shull PB, “Novel, soft, water-filled acoustic waveguides for simultaneous tactile force and location sensing,” IEEE Transactions on Industrial Electronics, In press, 2024.
20. Lin Y, Shull PB, Chossat JB, “Design of a wearable real-time hand motion tracking system using an array of soft polymer acoustic waveguides,” Soft Robotics, 11(2): 282-295, 2024.
21. Li J, Zhu K, Li D, Kang P, Shull PB, “3D knee and hip angle estimation with reduced wearable IMUs via transfer learning during yoga, golf, swimming, badminton, and dance,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32: 325-338, 2024.
22. Zhu K, Li J, Li D, Fan B, Shull PB, “IMU shoulder angle estimation: Effects of sensor-to-segment misalignment and sensor orientation error,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31: 4481-4491, 2023.
23. Kang P, Jiang S, Shull PB, “Synthetic EMG based on adversarial style transfer can effectively attack biometric-based personal identification models,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31: 3275-3284, 2023.
24. Sun T, Li D, Fan B, Tan T, Shull PB, “Real-time ground reaction force and knee extension moment estimation during drop landings via modular LSTM modeling and wearable IMUs,” IEEE Journal of Biomedical and Health Informatics, 27(7): 3222-3233, 2023.
25. Jiang S, Strout Z, He B, Peng D, Shull PB, Lo BPL, “Dual stream meta learning for road surface classification and riding event detection on shared bikes,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(11): 7188-7200, 2023.
26. Hafer JF, Vitali R, Gurchiek R, Curtze C, Shull PB, Cain SM, “Challenges and advances in the use of wearable sensors for lower extremity biomechanics,” Journal of Biomechanics, 157: 111714, 2023.
27. Chiasson D, Lin Y, Kok M, Shull PB, “Asynchronous hyperbolic UWB source-localization and self-localization for indoor tracking and navigation,” IEEE Internet of Things Journal, 10(13): 11655-11668, 2023.
28. Charlton JM, Xia H, Shull PB, Eng JJ, Li LC, Hunt MA, “Multi-day monitoring of foot progression angles during unsupervised, real-world walking in people with and without knee osteoarthritis,” Clinical Biomechanics, 105: 105957, 2023.
29. Tan T, Gatti AA, Fan B, Shea KG, Sherman SL, Uhlrich SD, Hicks JL, Delp SL, Shull PB, Chaudhari AS, “A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation,” Nature NPJ Digital Medicine, 6(1): 46, 2023.
30. Li D, Kang P, Zhu K, Li J, Shull PB, “Feasibility of wearable PPG for simultaneous hand gesture and force level classification,” IEEE Sensors Journal, 23(6): 6008-6017, 2023.
31. Kang P, Li J, Jiang S, Shull PB, “Reduce system redundancy and optimize sensor disposition for EMG–IMU multimodal fusion human–machine interfaces with XAI,” IEEE Transactions on Instrumentation and Measurement, 72: 2500209, 2023.
32. Farhadi F, Ou H, Shull PB, Johnson S, “Smart passive gait retraining intervention via pebbles for reducing peak plantar pressure: Short-term results,” Medicine in Novel Technology and Devices, 19: 100242, 2023.
33. Song X, Van De Ven SS, Liu L, Wouda FJ, Wang H, Shull PB, “Activities of daily living-based rehabilitation system for arm and hand motor function retraining after stroke,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30: 621-631, 2022.
34. Song X, Van De Ven SS, Chen S, Kang P, Gao Q, Jia J, Shull PB, “Proposal of a wearable multimodal sensing-based serious games approach for hand movement training after stroke,” Frontiers in Physiology, 13: 811950, 2022.
35. Tan T, Wang D, Shull PB, Halilaj E, “IMU and smartphone camera fusion for knee adduction and knee flexion moment estimation during walking,” IEEE Transactions on Industrial Informatics, 19(2): 1445-1455, 2022.
36. Tan T, Strout ZA, Cheung RTH, Shull PB, “Strike index estimation using a convolutional neural network with a single, shoe-mounted inertial sensor,” Journal of Biomechanics, 139: 111145, 2022.
37. Rokhmanova N, Kuchenbecker KJ, Shull PB, Ferber R, Halilaj E, “Predicting knee adduction moment response to gait retraining with minimal clinical data,” PLOS Computational Biology, 18(5): e1009500, 2022.
38. Kang P, Li J, Jiang S, Shull PB, “A visual variability and visuo-tactile coordination inspired child adaptation mechanism for wearable age group recognition and activity recognition,” Advanced Intelligent Systems, 5(1): 2200236, 2022.
39. Chiasson D, Shull PB, “Ultrawideband ranging in dynamic dense human networks,” IEEE Transactions on Human-Machine Systems, 52(6): 1327-1337, 2022.
40. Wang H, Kang P, Gao Q, Jiang S, Shull PB, “A novel PPG-FMG-ACC wristband for hand gesture recognition,” IEEE Journal of Biomedical and Health Informatics, 26(10): 5097-5108, 2022.
41. Ma CZH, Bao T, DiCesare CA, Harris I, Chambers A, Shull PB, Zheng YP, Cham R, Sienko KH, “Reducing slip risk: A feasibility study of gait training with semi-real-time feedback of foot-floor contact angle,” Sensors, 22(10): 3641, 2022.
42. Li J, Kang P, Tan T, Shull PB, “Transfer learning improves accelerometer-based child activity recognition via subject-independent adult-domain adaption,” IEEE Journal of Biomedical and Health Informatics, 26(5): 2086-2095, 2022.
43. Fan B, Li Q, Tan T, Kang P, Shull PB, “Effects of IMU sensor-to-segment misalignment and orientation error on 3-D joint angle estimation,” IEEE Sensors Journal, 22(3): 2543-2552, 2022.
44. Kang P, Li J, Fan B, Jiang S, Shull PB, “Wrist-worn hand gesture recognition while walking via transfer learning,” IEEE Journal of Biomedical and Health Informatics, 26(3): 952-961, 2021.
45. Shull PB, Xia H, Charlton JM, Hunt MA, “Wearable real-time haptic biofeedback foot progression angle gait modification to assess short-term retention and cognitive demand,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 3(29): 1858-1865, 2021.
46. Jiang S, Kang P, Song X, Lo B, Shull PB, “Emerging wearable interfaces and algorithms for hand gesture recognition: A survey,” IEEE Reviews in Biomedical Engineering, 15: 85-102, 2021.
47. Tan T, Strout ZA, Shull PB, “Accurate impact loading rate estimation during running via a subject-independent convolutional neural network model and optimal IMU placement,” IEEE Journal of Biomedical and Health Informatics, 25(4): 1215-1222, 2021.
48. Chossat JB, Shull PB, “Soft acoustic waveguides for strain, deformation, localization and twist measurements,” IEEE Sensors Journal, 21(1): 222-230, 2021.
49. Wang S, Mo S, Chung RCK, Shull PB, Ribeiro DC, Cheung RTH, “How foot progression angle affects knee adduction moment and angular impulse in people with and without medial knee osteoarthritis: a meta-analysis,” Arthritis Care & Research, 73(12): 1763-1776, 2021.
50. Fan B, Xia H, Xu J, Li Q, Shull PB, “IMU-based knee flexion, abduction and internal rotation estimation during drop landing and cutting tasks,” Journal of Biomechanics, 124: 110549, 2021.
51. Lindsey B, Xu J, Chiasson D, Shull PB, Cortes N, “Feasibility of wearable haptic biofeedback training for reducing the knee adduction moment during overground walking,” Journal of Biomechanical Engineering, 143(4): 044501, 2021.
52. Kang P, Jiang S, Shull PB, Lo B, “Feasibility validation on healthy adults of a novel active vibrational sensing based ankle band for ankle flexion angle estimation,” IEEE Open Journal of Engineering in Medicine and Biology, 2: 314-319, 2021.
53. Li C, Song X, Chen S, Wang C, He J, Zhang Y, Xu S, Yan Z, Jia J, Shull PB, “Long-term effectiveness and adoption of a cellphone augmented reality system on patients with stroke: randomized controlled trial,” JMIR Serious Games, 9(4): e30184, 2021.
54. Xia H, Huang Y, Chen G, Cheng S, Cheung RT, Shull PB, “Self-selected running gait modifications reduce acute impact loading, awkwardness, and effort,” Sports Biomechanics, 1-14, 2021.
55. Tan T, Strout ZA, Xia H, Orban M, Shull PB, “Magnetometer-free, IMU-based foot progression angle estimation for real-life walking conditions,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29: 282-289, 2020.
56. Xia H, Charlton JM, Shull PB, Hunt MA, “Portable, automated foot progression angle gait modification via a proof-of-concept haptic feedback-sensorized shoe,” Journal of Biomechanics, 107: 109789, 2020.
57. Xia H, Chen DKY, Zhu X, Shull PB, “Controlled slip energy harvesting while walking,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2(28): 437-443, 2020.
58. Shull PB, Xia H, “Modeling and prediction of wearable energy harvesting sliding shoes for metabolic cost and energy rate outside of the lab,” Sensors, 20(23): 6915, 2020.
59. Chiasson D, Xu J, Shull PB, “Lossless compression of human movement IMU signals,” Sensors, 20(20): 5926, 2020.
60. Jiang S, Gao Q, Liu H, Shull PB, “A novel, co-located EMG-FMG-sensing wearable armband for hand gesture recognition,” Sensors and Actuators A: Physical, 301: 111738, 2020.
61. Gao Q, Jiang S, Shull PB, “Simultaneous hand gesture classification and finger angle estimation via a novel dual-output deep learning model,” Sensors, 20(10): 2972, 2020.
62. Xu J, Cao F, Zhan S, Ling M, Hu H, Shull PB, “Mapping-based dosage of gait modification selection for multi-parameter subject-specific gait retraining,” IEEE Access, 8: 106354-106363, 2020.
63. Jiang S, Li L, Xu H, Xu J, GU GY, Shull PB, “Stretchable e-skin patch for gesture recognition on the back of the hand,” IEEE Transactions on Industrial Electronics, 67(1): 647-657, 2020.
64. Shull PB, Tan T, Culbertson HM, Zhu X, Okamura A, “Resonant frequency skin stretch for wearable haptics,” IEEE Transactions on Haptics, 12(3): 247-256, 2019.
65. Shull PB, Jiang S, Zhu Y, Zhu X, “Hand gesture recognition and finger angle estimation via wrist-worn modified barometric pressure sensing,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(4): 724-732, 2019.
66. Tan T, Chiasson DP, Hu H, Shull PB, “Influence of IMU position and orientation placement errors on ground reaction force estimation,” Journal of Biomechanics, 97: 109416, 2019.
67. Chossat JB, Chen DKY, Park YL, Shull PB, “Soft wearable skin-stretch device for haptic feedback using twisted and coiled polymer actuators,” IEEE Transactions on Haptics, 12(4): 521-532, 2019.
68. Song X, Chen S, Jia J, Shull PB, “Cellphone-based automated Fugl-Meyer assessment to evaluate upper extremity motor function after stroke,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(10): 2186-2195, 2019.
69. Charlton JM, Xia H, Shull PB, Hunt MA, “Validity and reliability of a shoe-embedded sensor module for measuring foot progression angle during over-ground walking,” Journal of Biomechanics, 89: 123-127, 2019.
70. Bao T, Su L, Kinnaird C, Kabeto M, Shull PB, Sienko K, “Vibrotactile display design: Quantifying the importance of age and various factors on reaction times,” PloS one, 14(8): e0219737, 2019.
71. Zhang JH, Chan ZY, Au IP, An WW, Shull PB, Cheung RT, “Transfer learning effects of biofeedback running retraining in untrained conditions,” Medicine and Science in Sports and Exercise, 51(9): 1904-1908, 2019.
72. Maglott J, Chiasson D, Shull PB, “Influence of skill level on predicting the success of one's own basketball free throws,” PloS one, 14(3): e0214074, 2019.
73. Huang Y, Xia H, Chen G, Cheng S, Cheung RTH, Shull PB, “Foot strike pattern, step rate, and trunk posture combined gait modifications to reduce impact loading during running,” Journal of Biomechanics, 86: 102-109, 2019.
74. Jiang S, Lv B, Guo W, Zhang C, Wang H, Sheng X, Shull PB, “Feasibility of wrist-worn, real-time hand and surface gesture recognition via sEMG and IMU sensing,” IEEE Transactions on Industrial Informatics, 14(8): 3376-3385, 2018.
75. Wang J, Xu J, Shull PB, “Vertical jump height estimation algorithm based on take-off and landing identification via foot-worn inertial sensing,” Journal of Biomechanical Engineering, 140(3): 034502, 2018.
76. Uhlrich SD, Silder A, Beaupre GS, Shull PB, Delp SL, “Subject-specific toe-in or toe-out gait modifications reduce the larger knee adduction moment peak more than a non-personalized approach,” Journal of Biomechanics, 66: 103-110, 2018.
77. Li L, Jiang S, Shull PB, Gu GY, “SkinGest: artificial skin for gesture recognition via filmy stretchable strain sensors,” Advanced Robotics, 1-10, 2018.
78. Xu J, Bao T, Lee UH, Kinnaird C, Carender W, Huang Y, Sienko KH, Shull PB, “Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept,” Journal of NeuroEngineering and Rehabilitation, 14(1): 102, 2017.
79. Xia H, Xu J, Wang J, Hunt MA, Shull PB, “Validation of a smart shoe for estimating foot progression angle during walking gait,” Journal of Biomechanics, 61: 193-198, 2017.
80. Shull PB, Zhu X, Cutkosky MR, “Continuous movement tracking performance to predictable and unpredictable tasks with vibrotactile feedback,” IEEE Transactions on Haptics, 10(4): 466-475, 2017.
81. Lin S, Xu J, Zhi X, Chen D, Miao J, Shull PB, Cui D, “Design and fabrication of a stretchable circuit board for wireless posture measurement,” IEEE Electron Device Letters, 38(3): 399-402, 2017.
82. Shull PB, Xu J, Yu B, Zhu X, “Magneto-gyro wearable sensor algorithm for trunk sway estimation during walking and running gait,” IEEE Sensors Journal, 17(2): 480-486, 2017.
83. Huang Y, Jirattigalachote W, Cutkosky MR, Zhu X, Shull PB, “Novel foot progression angle algorithm estimation via foot-worn, magneto-inertial sensing,” IEEE Transactions on Biomedical Engineering, 63(11): 2278-2285, 2016.
84. Huang Y, Xu J, Yu B, Shull PB, “Validity of Fitbit, Jawbone UP, Nike+ and other wearable devices for level and stair walking,” Gait & Posture, 48: 36-41, 2016.
85. Zhang D, Xu F, Xu H, Shull PB, Zhu X, “Quantifying different tactile sensations evoked by cutaneous electrical stimulation using electroencephalography features,” International Journal of Neural Systems, 26: 1650006, 2016.
86. Shull PB, Huang Y, Schlotman T, Reinbolt JA, “Muscle force modification strategies are not consistent for gait retraining to reduce the knee adduction moment in individuals with knee osteoarthritis,” Journal of Biomechanics, 48: 3163-3169, 2015.
87. Hernandez F, Shull PB, Camarillo DB, “Evaluation of a laboratory model of human head impact biomechanics,” Journal of Biomechanics, 48: 3469-3477, 2015.
88. Shull PB, Damian DD, “Haptic wearables as sensory replacement, sensory augmentation and trainer–a review,” Journal of Neuroengineering and Rehabilitation, 12(1), 59, 2015.
89. Zhang D, Xu H, Shull PB, Liu J, Zhu X, “Somatotopical feedback versus non-somatotopical feedback for phantom digit sensation on amputees using electrotactile stimulation,” Journal of Neuroengineering and Rehabilitation, 12(1), 44, 2015.
90. Shull PB, Jirattigalachote W, Hunt MA, Cutkosky MR, Delp SL, “Quantified self and human movement: A review on the clinical impact of wearable sensing and feedback for gait analysis and intervention,” Gait & Posture, 40: 11-19, 2014.
91. Sui J, Shull PB, Ji L, “Pilot study of vibration stimulation on neurological rehabilitation,” Bio-medical Materials and Engineering, 24(6): 2593-2601, 2014.
92. Shull PB, Silder A, Shultz R, Besier TF, Delp SL, Cutkosky MR, “Six-week gait retraining program reduces knee adduction moment, reduces pain, and improves function for individuals with medial compartment knee osteoarthritis,” Journal of Orthopaedic Research, 31(7): 1020-1025, 2013.
93. Shull PB, Shultz R, Silder A, Besier TF, Cutkosky MR, Delp SL, “Toe-in gait reduces the first peak in the knee adduction moment during walking in knee osteoarthritis patients,” Journal of Biomechanics, 46: 122-128, 2013.
94. Camarillo DB, Shull PB, Mattson J, Shultz R, Garza D, “An instrumented mouthguard for measuring linear and angular head impact kinematics in American football,” Annals of Biomedical Engineering, 41(9): 1939-1949, 2013.
95. Tenforde AS, Shull PB, Fredericson M, “Neuromuscular prehabilitation to prevent osteoarthritis after a traumatic joint injury,” Physical Medicine and Rehabilitation, 4: S141-144, 2012.
96. Shull PB, Lurie K, Cutkosky MR, Besier TF, “Training multi-parameter gaits to reduce the knee adduction moment with data-driven models and haptic feedback,” Journal of Biomechanics, 44(8): 1605-1609, 2011.
97. Wheeler JW, Shull PB, Besier TF, “Real-time knee adduction moment feedback for gait retraining through visual and tactile displays,” Journal of Biomechanical Engineering, 133(4): 041007, 2011.
98. Bark K, Wheeler JW, Shull PB, Savall J, Cutkosky MR, “Rotational skin stretch feedback: a wearable haptic display for motion,” IEEE Transactions on Haptics, 3(3): 166-176, 2010.
99. Shull PB, Gonzalez RV, “Real-time haptic-teleoperated robotic system for motor control analysis,” Journal of Neuroscience Methods, 151(2): 194-199, 2006.

Conference Articles
1. Pan H, Li D, Chen C, Jiang S, Shull PB, “An adversarial learning framework for reliable myoelectric force estimation under fatigue,” IEEE International Conference on Robotics and Automation (ICRA), pp. 482-488, 2025.
2. Xu C, Tan Y, Strout Z, Liu G, Zhu K, Shull PB, “Real-time open source kinematic estimation with wearable IMUs,” IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 301-307, 2025.
3. Tan Y, He X, Liu G, Zhong L, Pan H, Zhu K, Shull PB, “Transformer-based full-body pose estimation for rehabilitation via RGB camera and IMU fusion,” IEEE International Conference on Body Sensor Networks (BSN), 2025.
4. Wang H, Li D, Liang K, Shull PB, “Subject-independent ankle joint power estimation with two IMUs during flat and inclined walking,” IEEE International Conference on Body Sensor Networks (BSN), 2023.
5. Kang P, Zhu K, Jiang S, He B, Shull PB, “HBOD: A novel dataset with synchronized hand, body, and object manipulation data for human-robot interaction,” IEEE International Conference on Body Sensor Networks (BSN), 2023.
6. Lin Y, Alemu M, Shull PB, “Investigation of soft acoustic waveguide dispersion for wearable strain sensing in human motion monitoring,” International Conference on Intelligent Robotics and Applications, pp. 238-249, 2023.
7. Alemu M, Lin Y, Shull PB, “Design and fabrication of an artificial skin integrated with soft ultrasonic waveguides for finger joint motion detection,” International Conference on Intelligent Robotics and Applications, pp. 206-218, 2023.
8. Lin Y, Chiasson D, Shull PB, “Wearable water-filled soft transparent pressure sensor based on acoustic guided waves,” IEEE International Ultrasonics Symposium (IUS), pp. 1-4, 2022.
9. Xia H, Kwon J, Pathak P, Ahn J, Shull PB, Park YL, “Design of a multi-functional soft ankle exoskeleton for foot-drop prevention, propulsion assistance, and inversion/eversion stabilization,” IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), pp. 118-123, 2020.
10. Song X, Ding L, Zhao J, Jia J, Shull PB, “Cellphone augmented reality game-based rehabilitation for improving motor function and mental state after stroke,” IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2019.
11. Maglott J, Shull PB, “Wearable occlusion device for assessing cognitive basketball shooting performance between males and females,” Proceedings of the International Conference on Industrial Control Network and System Engineering Research, pp. 37-41, 2019.
12. Peng D, Strout Z, Jiang S, Shull PB, “A road condition classifier via lock embedded IMU on dock-less shared bikes,” Proceedings of the International Conference on Industrial Control Network and System Engineering Research, pp. 32-36, 2019.
13. Chen DKY, Chossat JB, Shull PB, “HaptiVec: Presenting haptic feedback vectors in handheld controllers using embedded tactile pin arrays,” ACM CHI Conference on Human Factors in Computing Systems, 2019.
14. Shull PB, Xia H, “Energy harvesting modeling and prediction during walking gait for a sliding shoe,” 23rd IEEE International Conference on Digital Signal Processing (DSP), 2018.
15. Zhu Y, Jiang S, Shull PB, “Wrist-worn hand gesture recognition based on barometric pressure sensing,” IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp. 181-184, 2018.
16. Xia H, Shull PB, “Preliminary testing of an angled sliding shoe for potential human energy harvesting applications,” 2nd International Conference on Robotics and Automation Sciences, pp. 147-150, 2018.
17. Xu J, Lee UH, Bao T, Huang Y, Sienko KH, Shull PB, “Wearable sensing and haptic feedback research platform for gait retraining,” IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp. 125-128, 2017.
18. Maglott JC, Xu J, Shull PB, “Differences in arm motion timing characteristics for basketball free throw and jump shooting via a body-worn sensorized sleeve,” IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp. 31-34, 2017.
19. Ling Li, Jiang S, Tao Y, Shull PB, Gu GY, “Fabrication and testing of a filmy “feelingless” stretchable strain sensor,” IEEE/SICE International Symposium on System Integration (SII), pp. 362-367, 2017.
20. Jiang S, Bo Lv, Sheng X, Zhang C, Wang H, Shull PB, “Development of a real-time gesture recognition wristband based on sEMG and IMU sensing,” IEEE International Conference on Robotics and Biomimetics, 2016.
21. Chen DKY, Xu J, Shull PB, Besier TF, “Tactile apparent movement as a modality for lower limb haptic feedback,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp. 373-383, 2016.
22. Yu B, Bao T, Zhang D, Carender W, Sienko KH, Shull PB, “Determining inertial measurement unit placement for estimating human trunk sway while standing, walking and running,” 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC, 2015.
23. Huang Y, Guo W, Liu J, He J, Xia H, Sheng X, Wang H, Feng X, Shull PB, “Preliminary testing on a hand gesture recognition wristband based on EMG and inertial sensor fusion,” 8th International Conference on Intelligent Robotics and Applications, 2015.
24. Zhang B, Shull PB, Zhang D, “A simulation study on nerve block by electrical stimulation with high frequency,” 9th International Convention on Rehabilitation Engineering & Assistive Technology, 2015.
25. Shull PB, Jirattigalachote W, Zhu X, “An overview of wearable sensing and wearable feedback for gait retraining,” International Conference on Intelligent Robotics and Applications, pp. 434-443, 2013.
26. Jirattigalachote W, Shull PB, Cutkosky MR, “Virtual pebble: a haptic state display for pedestrians,” IEEE Ro-Man Symposium, pp. 401-406, 2011.
27. Lurie KL, Shull PB, Nesbitt KF, Cutkosky MR, “Informing haptic feedback design for gait retraining,” IEEE World Haptics, pp. 19-24, 2011.
28. Rantala J, Myllymaa K, Raisamo R, Lylykangas J, Surakka V, Shull PB, Cutkosky MR, “Presenting spatial tactile messages with a hand-held device,” IEEE World Haptics, pp. 101-106, 2011.
29. Shull PB, Lurie KL, Shin M, Besier TF, Cutkosky MR, “Haptic gait retraining for knee osteoarthritis treatment,” IEEE Haptics Symposium, pp. 409-416, 2010.
30. Shull PB, Bark K, Cutkosky MR, “Skin nonlinearities and their effect on user perception for rotational skin stretch,” IEEE Haptics Symposium, pp. 77-82, 2010.
31. Lurie KL, Manual J, Shull PB, “Haptic motion training: exploring learning environments for a portable gait retraining system,” IEEE International Symposium on Haptic Audio-Visual Environments and Games, pp. 1-6, 2010.
32. Shull PB, Niemeyer G, “Open-loop bilateral teleoperation for stable force tracking,” IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5121-5126, 2009.
33. Shull PB, Niemeyer G,” Force and position scaling limits for stability in force reflecting teleoperation,” ASME Dynamic Systems and Control Conference, pp. 607-614, 2008.
34. Hart JS, Shull PB, Gentry D, Niemeyer G, Roderick S, Akin D, “Wave-variable based force feedback for a space-qualified telerobot,” ASME Dynamic Systems and Control Conference, 303-310, 2008.
35. Shull PB, Niemeyer G, “Experiments in local force feedback for high-inertia, high-friction telerobotic systems,” ASME International Mechanical Engineering Congress and Exposition, pp. 1241-1246, 2007.
36. Awwal AAS, Ferguson WS, Shull PB, “Best angle to orient two intersecting lines," SPIE, pp. 63100-63111, 2006.

Design and Manufacturing II (ME209), Wearable Systems (ME26012)

1. Deputy Editor: Journal of NeuroEngineering and Rehabilitation, 2025-
2. Associate Editor: Nature npj Digital Medicine, 2022-
3. Associate Editor: IEEE Journal of Biomedical and Health Informatics, 2021-2025
4. Associate Editor: IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017-2025
5. Associate Editor: Wearable Technologies, 2019-2024
6. Associate Editor: Special Issue, Frontiers in Physiology: Wearable Sensing of Movement Quality after Neurological Disorders, 2022
7. Technical Committee Member: IEEE Engineering in Medicine and Biology (EMB) Technical Committee on Wearable Biomedical Sensors and Systems, 2017-2024
8. Technical Committee Member: IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2019
9. Technical Committee Member and Session Chair: International Conference on Robotics and Automation Sciences, Wuhan, China, June 2018
10. Editorial Board Member: IEEE Open Journal of Engineering in Medicine and Biology, 2019-
11. Conference Session Chair: International Society of Biomechanics, Brisbane, Australia, July 2017 Session Title: Injury and Rehabilitation.

2025 Shanghai Jiao Tong University President’s Award
2020, 2018, 2015 Shanghai Jiao Tong University Mechanical Engineering Department Excellent
Researcher Award (Top 10%)
2017 Outstanding Researcher Award, United States National Institutes of Health (NIH) National
Center for Simulation in Rehabilitation
2017 Shanghai Jiao Tong University Candlestick Excellence in Teaching Award
2014 Shanghai Young Talents Award Recipient
2012 Feature Article in United States National Science Foundation's Online Magazine Science
Nation, “Movement Retraining Can Reduce Knee Pain"
2011 Stanford - Tsinghua Visiting Scholar Award Recipient

Wearable Systems Lab