PERSONALIZED MODELS AND HEALTH MAINTENANCE FOR MOBILITY Fregly and Rodgers.
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Transcript of PERSONALIZED MODELS AND HEALTH MAINTENANCE FOR MOBILITY Fregly and Rodgers.
PERSONALIZED MODELS AND HEALTH MAINTENANCE FOR MOBILITY
Fregly and Rodgers
Overview
Personalized Models Health Maintenance Gaps Summary
Overview
Personalized Models Motivation Personalized modeling methods Full-body scan for personalized model
creation Customization of robot function using
personalized models Health Maintenance Gaps Summary
Why Personalized Models?
“One size fits none” - everyone is different! Increases objectivity in treatment planning
(different clinicians may plan different treatments given same patient data).
Can facilitate identification of previously unknown treatments (e.g., modified gait to treat knee OA).
May permit identification of best treatment option for a specific patient.
May permit identification of sensitive treatment parameters (i.e., which parameter values do clinicians need to “get right”?)
Highly Variable Outcomes
For some treatments, standard deviation in outcome is bigger than the effect size.
Where modelsshould be focused
Where problems aretoo complex for models
Scope of model applicability must be properly defined.
HIGH FIDELITY ANATOMIC SHOULDER & ELBOW MODELFrans C.T. van der Helm, Ph.D., Delft
Delft Shoulder and Elbow Model High fidelity anatomic musculoskeletal
model constructed from extensive measurements performed on a single cadaver specimen.
Model accounts for more variables (including sarcomere length) than any other upper extremity model.
Model validation: Muscle forces cannot be measured, so no strict validation!
The same model personalization approach cannot be performed on living patients.
Model Applications
Glenohumeral arthrodesis Glenohumeral endoprosthesis Tendon transfer after brachial plexus lesion “Reverse” shoulder endoprosthesis Scapula fractures Functional electrical stimulation for tetraplegics Neurological disorders Computer Assisted Surgical Planning (CASP) Wheelchair propulsion Garbage collection Brick-layering
ORTHOPAEDIC SURGERY AND REHABILITATIONMaria Benedetti, M.D., Alberto Leardini, Ph.D., and Marco Viceconti, Ph.D. - Bologna
Possible Uses of Gait Analysis Assessment – Assess after treatment how the
treatment worked for a group of patients. (Common)
Identification – Identify on an individual patient basis which patients should be treated (but not how they should be treated). (Becoming more common)
Prediction – Predict on an individual patient basis which treatment should be performed and how it should be performed (where personalized models may help). (Does not yet happen)
The potential value of Prediction depends on the clinical problem at hand.
Clinical Example for Prediction Clinical Situation: Oncological patients who
receive a limb salvage procedure. Problem: How to get the bone allograft to heal
– it needs load to repair but not so much that it breaks.
Observation: Each case is unique – surgical and rehabilitation design are not stereotypical.
Proposed solution: Treatment design using gait and imaging data in a personalized musculoskeletal model that estimates muscle & bone loads.
Challenge: How to gain confidence in patient-specific predictions of muscle & bone loads?
Personalized Model Creation & Use
Valente et al., Computer Aided Medicine Conference, 2010
Design of Total Ankle Replacement
Though not personalized, design developed using patient data and modeling methods.
Leardini et al., Clin Orthop Relat Res, 2004
PATIENT-SPECIFIC MUSCULOSKELETAL MODELS
Bart Koopman, Ph.D., Enschede
Model Personalization
Problem: Most musculoskeletal models are generic, and uniform scaling is inaccurate.
Solution: Scale/deform a generic parametric model to match each patient. Image based scaling of bone geometry (CT, MRI) Functional kinematic scaling of joint
positions/orientations (marker-based motion, laser scans, inertial sensors)
Functional dynamic scaling of muscle strength (dynamometers)
Challenge: Fusion of data from different modalities.
Model Utilization
Collect pre-treatment imaging, kinematic, and dynamic data.
Simulate surgical scenarios and parameters. Select scenario and parameters that
optimize post-treatment outcome. Implement plan in surgical navigation
system. Validate model predictions using surgical
cases not planned with model. Example: Which tendon to transfer
to restore hip abduction strength in patients with Trendelenburg gait?
3D PERSONALIZED MUSCULOSKELETAL MODELS
Waffa Skalli, Ph.D., Paris
Research Goal
Multiscale personalized human musculoskeletal models that enable: Early detection of balance abnormalities. Design of innovative devices for
prevention and treatment of musculoskeletal disorders.
Identification of the source of pathology (e.g., is it muscular or skeletal?).
Quantitative assessment of treatment strategies.
Personalized Modeling
Personalized spine models for studying scoliosis Partners: Hospitals in Paris, Saint Etienne, and Montreal
Biplane X-ray Modeling Technology
Internal-External Registration
Direct registration of presonalized skeletal models to external marker locations for gait analysis.
Bi-plane X-rays with External Markers Gait Data
Where are the bones with respect to the skin markers?
HOCOMA - ADVANCED FUNCTIONAL MOVEMENT THERAPYPeter Hostettler, PhD & CEO, and team, Zurich
Future Directions
Neurorehabilitation is current focus. Orthopaedic rehabilitation viewed as a
potentially big future market. Current robotic training system designed
using the gait pattern of one of the designers.
Customization of robot to individual patients could be valuable in the the future (with possible role of personalized personalized modeling).
Overview
Personalized Models Health Maintenance
Remote monitoring Remote training & treatment Prediction modeling
Gaps Summary
REMOTE MONITORING AND REMOTELY SUPERVISED TRAINING & TREATMENT
Hermie Hermens, PhD, Enschede
Remote Health Care Vision
Goal: Create new health care services by combining biomedical engineering with information and communication technology.
“Enabling monitoring and treatment of subjects anywhere, anytime and intervene when needed.”
Remote monitoring – Remote measurement of vital biosignals without interfering with daily activities.
Remotely supervised training & treatment – monitoring + feedback that enable a patient to train when and where convenient and with the same quality of training as in a clinical environment.
Benefits Remote Monitoring
Less intramural care (costs) More freedom for patient Peace of mind
Remotely Supervised Treatment High intensity training possible (more = better) Training in natural environment translates to more
effective training Puts patient in driver seat Clinician can ‘treat’ several patients at the same
time Main challenges are technological feasibility
and clinical/patient acceptance.
Example: Tele-Treatment of Chronic Back Pain
Studies report a change in activity level due to chronic back pain.
Clinical study: 29 chronic back pain patients and 20 asymptomatic controls
Activity levels monitored for 7 consecutive days using an 3D inertial motion sensor
Overall activity levels the same but activity patterns different between groups.
Will normalization of activity patterns through feedback improve outcome? (Clinical trial running)
Example: Tele-Treatment of Neck/Shoulder Pain
Chronic shoulder/neck pain typically shows no clear physiological overloading.
Solution: Design a remote feedback system to warn patients when insufficient relaxation occurs.
Muscle relaxation assessed via surface EMG with real-time feedback provided to patient and therapist.
100 patients treated in Belgium, Germany, Sweden, and the Netherlands
Outcome as good as classic treatment
Approach appreciated by patients and therapists
INSTITUT FOR SUNDHEDSVIDENSKAB OG TEKNOLOGIAALBORG UNIVERSITYAALBORG, DENMARK
DEPT. OF HEALTH SCIENCE AND TECHNOLOGY
TeleKat project applies User Driven Innovation to develop wireless telehomecare technology enabling COPD patients to perform self-monitoring of their status, and to maintain rehabilitation activities in their homes.
TeleKat COPD (KOL)
Brian Caulfield, Academic Director
•Technology to monitor older adults•Systems deployed to 620 people•Building Predictive models based on data collected
TRIL Gait Analysis Platform (GAP) consists of:• Pressure sensing walkway (Tactex, S4 Sensors, Victoria, BC, Canada)• Two SHIMMER™ kinematic sensors worn on the subject’s shanks• Two orthogonally mounted web cameras
Unobtrusive capture of gait parameters and physiological data in 600 patients.
Data used develop diagnostics capabilities to detect increased gait variability & unsteadiness in elderly people (Predicting fall risk to 85% accuracy).
Can help with early identification of onset of diseases such as Parkinson’s
Gait Analysis Platform (GAP)
Wellness and Exercise
A complete home/work technology platform has been developed for the project, using a wearable wireless sensors system (SHIMMERs™) and an open shareable software platform (BioMOBIUS™).
This facilitates effective monitoring and biofeedback during exercise whilst enhancing end-user motivation and involvement in the process.
Balance & Strength Exercise Balance and Strength Exercise (BaSE) program
includes console-based system installed in each of the participant’s homes.
System guides the user through each of their exercises, reminding them of correct way to execute each movement.
System prompts participant to carry out prescribed number of exercise repetitions.
Using a combination of camera and kinematic sensors, BaSE system provides real-time feedback to participant on their performance and transmits data collected to the physiotherapist.
Allows monitoring and modification of prescribed exercise programs between clinic visits.
Overview
Personalized Models Health Maintenance Gaps Summary
Gaps for Personalized Modeling
How to validate model predictions (especially for internal quantities such as muscle, joint, and bone loads)?
How to calibrate “unobservable” parameters to which model predictions are sensitive?.
How to create personalized neural control models?
How to make generation of model-based predictions fast and easy for a clinical setting?
Gaps for Health Maintenance
User-centered development Effective technology transfer Demonstration of efficacy Need for models to identify predictive
variables
Overview
Personalized Models Health Maintenance Gaps Summary
Summary for Personalized Modeling
We have lots of technology! What we need are better ways to predict how to use technology to achieve significant improvements in mobility for specific patients and impairments.
Personalized modeling is one option for predicting how to use technology more effectively.
Creating personalized musculoskeletal models is not enough – we also need to include personalized neural control/neuroplasticity models so that patient responses to possible treatments can be predicted.
Summary for Health Maintenance
Technology for monitoring in progress Collaborations world-wide Need for user-centered development Predictive models needed