UR Medicine Motion Laboratories’ Post

#DeepLearning, a branch of artificial intelligence, involves using complex neural networks to process and analyze vast amounts of data. Its depth and complexity enable it to tackle tasks that are challenging for humans and traditional machine learning methods, thereby better assisting professionals in making decisions. At our wearable lab, we are leveraging deep learning models to classify activities of spine patients using signals from #wearable devices. This allows us to monitor the patients’ continuous activities at home accurately, offering valuable insights that support the rehabilitation process. #WearableTech #ActivityClassification #HealthcareInnovation #MotionAnalysis #Innovation #URochesterResearch #BiomedicalEngineering #BME #MovementAnalysis University of Rochester School of Medicine and Dentistry University of Rochester BME (Biomedical Engineering) University of Rochester University of Rochester Medical Center American Academy of Orthopaedic Surgeons (AAOS) American Physical Therapy Association (APTA) Orthopaedic Research Society Goergen Institute for Data Science (GIDS)

Ankle sprains account for approximately 16-40% of all lower limb sports-related injuries. #AnkleSprains occur when the ligaments that hold the ankle bones together are forced beyond their normal range of motion due to an abnormal roll, twist, or turn of the ankle. Many athletes experience persistent residual symptoms and injury recurrence.  Our Injury Prevention and Tactical Athlete Lab uses 3D motion capture to assess kinematic variables include ankle, knee, hip, pelvis, and trunk ranges of motion during athletic activities. As a result of this detailed analysis, physical therapists and physicians will be able to provide their patients with individualized treatment and define the period of time when the athlete may return to sport. #URochesterResearch #Kinematics #SportsBiomechanics #MotionLab #AnkleSprain University of Rochester School of Medicine and Dentistry University of Rochester University of Rochester Medical Center American Academy of Orthopaedic Surgeons (AAOS) Judy Baumhauer Sam Flemister David Ciufo Benedict DiGiovanni

Shoulder #Osteoarthritis is a chronic and often debilitating condition that affect as much as a third of those who are 60 and older to some degree. As the labrum wears down over time, it can lead to painful bone-on-bone friction, limited range of motion, and decreased mobility. Individuals suffering from shoulder osteoarthritis may experience persistent pain, stiffness, and difficulty performing everyday tasks. When shoulder osteoarthritis patients are referred to our lab, the utilization of dynamic Electromyography (#EMG) allows for the accurate measuring of neuromuscular activation during various everyday activities. These signals can then be analyzed to determine specific areas of weakness, delay, or efficacy present in the shoulder. This allows our healthcare providers to create a more personalized and effective treatment plan, leading to a higher quality clinical outcome for patients. #URochesterResearch University of Rochester School of Medicine and Dentistry University of Rochester BME (Biomedical Engineering) University of Rochester American Academy of Orthopaedic Surgeons (AAOS) Orthopaedic Research Society American Shoulder and Elbow Surgeons American Physical Therapy Association (APTA) Ilya Voloshin Gregg Nicandri Sandeep Mannava, MD, PhD Robert Bronstein Michael Maloney

Stress fractures account for up to 20% of all sports medicine clinic injuries. Stress fractures are injuries typically in the lower extremities, caused by repetitive loading during activities such as running resulting in pain. When muscles are fatigued, more stress is put on the bones allowing microscopic fractures to occur. Our lab offers advanced 3D running evaluations for runners and athletes of all ages. Lower extremity injuries like stress fractures can alter running mechanics causing asymmetry in gait. Kinematic variables like peak hip adduction, peak knee internal rotation, and knee adduction can be analyzed using our motion capture system to track progression back to sport after a stress fracture. #URochesterResearch #Kinematics #Runners #Athletes #StressFracture University of Rochester School of Medicine and Dentistry University of Rochester University of Rochester BME (Biomedical Engineering) American Orthopaedic Society for Sports Medicine The International Society of Arthroscopy, Knee Surgery and Orthopaedic Sports Medicine (ISAKOS) American Medical Society for Sports Medicine NCAA #Trackandfield #CrossCountry #5K #Marathon

Congratulations to our interns who have completed an intense and busy summer internship with us. A group of this caliber, which turns the pain into growth, is certain to be the future leaders in the medical field. If you are interested in joining our dynamic and ambitious team, please PM us.

Our database system enables efficient data storage by organizing all collected data from our labs, including EEG, EMG, IMU, kinetics, and kinematics data, ensuring easy retrieval. Clinical data is also integrated from multiple sources, including eRecords, eView, and patient charts, to create a comprehensive view of each patient, including patient demographic, radiographic, and patient reported outcomes, visit dates, surgical outcomes, and follow-up information. Rigorous quality checks are implemented to ensure data accuracy and completeness through validation rules and automated scripts. Scientists can easily retrieve specific data sets for analysis, using queries based on criteria and data type. Advanced data science techniques, including statistical analysis and machine learning, are applied to derive insights from the collected data This unified platform empowers us to unlock deeper insights into patient clinical outcomes and continuously refine our treatment approaches. #MotionAnalysis #Innovation #URochesterResearch #BiomedicalEngineering #BME #MovementAnalysis University of Rochester School of Medicine and Dentistry University of Rochester BME (Biomedical Engineering) University of Rochester University of Rochester Medical Center American Academy of Orthopaedic Surgeons (AAOS) American Physical Therapy Association (APTA) Orthopaedic Research Society Goergen Institute for Data Science (GIDS)

Thoracic Outlet Syndrome (TOS) is caused by the compression of nerves or blood vessels at the ring formed by the top ribs. Its symptoms include neck and shoulder pain, weakened grip, swelling and coldness of the affected limb, and tingling and numbness of the fingers. At out Labs, we are assessing the disability and function of TOS patients in everyday activities, which can provide objective and detailed information to physicians and #PhysicalTherapists (PTs) gauge the state of the patients thorough their treatment. As a result of analyzing the kinematics of TOS patients before and after their treatment, we can provide physicians and physical therapists with valuable biomechanical and clinical information, which will allow them to provide the best treatment possible. #URochesterResearch #Biomechanics American Shoulder and Elbow Surgeons American Physical Therapy Association (APTA) University of Rochester School of Medicine and Dentistry University of Rochester BME (Biomedical Engineering) University of Rochester American Academy of Orthopaedic Surgeons (AAOS) Orthopaedic Research Society Ilya Voloshin Gregg Nicandri Sandeep Mannava, MD, PhD Robert Bronstein Michael Maloney

Adult degenerative scoliosis is a sideways curve in the spine that develops in adults due to spinal degeneration and usually affects people 40 years of age or older. Moreover, it is considered a musculoskeletal disorder that can cause a lateral curve in the spine and can lead to physical limitations that may qualify for disability benefits: This increased stress and pain in the back and spine often results in compensation and altered neuromuscular activity in these patients. Our lab utilizes electromyography (EMG) to track the neuromuscular activity of degenerative scoliosis patients during a series of everyday tasks. This analysis helps the spine team (Varun Puvanesarajah, Robert Molinari, Paul Rubery, and Ashley Rogerson, Ram Haddas, PhD, MBA) to better understand the patient’s limitations with regards to the utilization of their spine and any specific areas of weakness that may be present. #URochesterResearch #AdultDegenerativeScoliosis #EMG #MotionCapture University of Rochester BME (Biomedical Engineering) University of Rochester Medical Center University of Rochester School of Medicine and Dentistry American Academy of Orthopaedic Surgeons (AAOS) Orthopaedic Research Society American Physical Therapy Association (APTA) Scoliosis Research Society North American Spine Society

Innovative tools and technologies could increase the effectiveness of rehabilitation and physical training outcomes. Two of our labs heavily use immersive environments using cutting-edge technologies. In our Fall Prevention & Balance lab, we challenge patients’ vestibular and somatosensory abilities through insights in balance and postural control. In our Virtual Reality lab, we create an immersive experience through the integration of advanced motion capture and instrumented treadmills for patients with lower and upper extremity disabilities. Gamification has the potential to revolutionize rehabilitation by increasing patient’s engagement, making therapy sessions enjoyable, and personalize treatment. #Rehabilitation #PhysicalTherapy #Innovation #HealthcareTech #CDP #VirtualReality #MotionLabs #Gamification #PatientCare University of Rochester School of Medicine and Dentistry University of Rochester BME (Biomedical Engineering) American Academy of Orthopaedic Surgeons (AAOS) American Physical Therapy Association (APTA) Orthopaedic Research Society Mary Ann Mavrinac Studio X - University of Rochester

Clinical data quality checks involve a combination of data validation techniques, statistical analyses, and machine learning models to ensure accuracy, consistency, and reliability. At our labs, we utilize rule-based and constraint-based validation to check data ranges, formats, and mandatory fields. Statistical models are essential for quality checks, leveraging descriptive statistics to identify outliers. Additionally, regression analyses monitor data trends over time to identify quality issues and detect outliers. Advanced machine learning models, such as Isolation Forest and One-Class SVM, are used for anomaly detection, effectively flagging data points that deviate from expected patterns. Classification models such as Random Forest, Logistic Regression, and Support Vector Machines ensure consistency by accurately categorizing data and spotting discrepancies. These steps assist in cleaning and preparing data for further advanced analysis, minimizing the risk of inaccuracies that could compromise clinical outcomes. #MotionAnalysis #Innovation #URochesterResearch #BiomedicalEngineering #BME #MovementAnalysis University of Rochester School of Medicine and Dentistry University of Rochester BME (Biomedical Engineering) University of Rochester University of Rochester Medical Center American Academy of Orthopaedic Surgeons (AAOS) American Physical Therapy Association (APTA) Orthopaedic Research Society Goergen Institute for Data Science (GIDS)