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Santos Know How
-Why Santos the Human Digital Twin?
Santos Technical Knowledge
–Access the Santos repository:
-Publications
-Books
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Santos Technical Papers
Simulation Products
Presentations
Client Applications
Santos as an Integrated Human Digital Twin
- 2003
- 2004
- 2005
- 2006
- 2007
- 2008
- 2009
- 2010
- 2011
- 2012
- 2013
- 2014
- 2015
- 2016
- 2017
- 2018
- 2019
- 2020
- 2021
- 2022
- 2023
- 2024
Not in commercial software
Current R&D Efforts R&D Efforts
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Robotics
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Posture Prediction
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Strength and Torque at Joint Modeling
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Army Combat Fitness Test
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Optimization |
Ergonomics |
Static Fatigue Modeling
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Dynamic Fatigue Modeling
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Interactive
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Human Factors
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Real time
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Reach Envelopes
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Task simulation: scenario generation
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Injury prediction: MSK, wearables, AI
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High fidelity
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Vision Models
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Physiology: Energy, work, Fatigue, Strength, etc.
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CAD import
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Human mass and inertia estimation
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US Army SSTAF Integration
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Biomechanics Models
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Thermal, hydration, energy
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AI/Cognitive
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Hand modeling and & grasping
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Human Physics: Predictive dynamics
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Unreal Engine
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Dual Arm Coordination
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Walking, running, lifting, load carriage, climbing, etc.
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GruntSim: ETOWL
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Human Performance Cost Functions: Energy, Discomfort, Effort
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Thermal: transient and steady state
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Behavior
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Soft and Deformable Clothing
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Stability and Balance
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Artificial intelligence – Deep Learning
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Realism Anthropometry Physics based |
Human Vibration Modeling and Analysis
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Neural Networks for human performance
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PPE and Armor Survivability Modeling and Assessment
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Muscle Activation
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API and Plug-inns
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Motion Capture: EKTIMO Markerless MoCap
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Validation |
Validation |
Validation |
Validation |
Santos as an Integrated Human Digital Twin
- Access the Santos repository:
- Publications
- Books
- Presentations
Case Studies
- Access the API manual
- Access the Plugins manual
- Tutorials
- Manuals
- eSupport
- Customer success
The following are case studies
- Case 1: US Army uses Santos for the Army Combat Fitness Test (ACFT)
- Case 2: Armor assessment for Special Forces (Hardwire)
- Case 3: OVERMATCH for US Army Futures Command Data Analysis Center (DAC)
- Case 4: Extended load carriage (load configuration on Santos for 16 mile hike)
- Case 5: US Marines uses SoldierSim to assess new products
- Case 6: Auto manufacturer uses Santos to conduct analysis on assembly line
- Case 7: University of Iowa athletics uses iPredict to mitigate injuries
- Case 8: US Army Center for the Intrepid uses Santos as a prosthetic assessment/training tool
- Case 9: Disney uses Santos for clothing design and comfort analysis
Human Performance: Case Study Army Combat Fitness Test Test
The ACFT replaces the Army Physical Fitness Test, which was developed in 1980 and has not been significantly modified since its creation. The old test consisted of three elements: push-ups, sit-ups, and a two-mile run. The ACFT, designed by the Army to better connect soldiers’ fitness levels with combat readiness and to reduce preventable injuries and attrition.
The Army awarded a contract to the university to evaluate the quality, comprehensiveness, and accuracy of the Army Baseline Soldier Physical Readiness Requirements Study used to develop the new Army Combat Fitness Test (ACFT), which Army personnel must take twice annually. Using SANTOS®, Iowa will also develop and refine scoring standards for each ACFT test event across all levels of physical demand (moderate, significant, heavy) associated with various military occupational specialties.
Army Combat Fitness Test
Santos was selected by the US Military to be the external validation for the Army Combat Fitness Test. Over a 4-year period, the team worked to validate and correlate
(b) External validation
The goal is to compare the tasks needed for the Common Soldier Tasks (CST) and Battle Drills (BD) with those in the Army Combat Fitness Test.
Have subjects conduct the various movements of the ACFT, CST and BD while using a motion capture system to measure joint angles and torques on the joints.
Finally, estimate the gold (moderate) threshold for the ACFT events by comparing the physiological and motion requirements of corresponding CSTs and BDs.
Case Study
- Combat Fitness Test
- Soldier Common Tasks
- EnduranceStrengthVO2FatigueEnergy
- High Crawl
- Endurance
- Strength
- VO2
- Fatigue
- Energy
At today’s athletics organizations and military units alike, the veracity of data generated on a daily basis is massive. Daily tests, sensors that track the person’s load are monitored at 100 Hz (data collected 100 times per second). Medical records, sleep, stress, and many other known parameters are also collected.
This massive data a good understanding of the athlete or soldier at a a certain instance in time, furthermore, across an entire season.
This data is used train a Machine Learning system.
The intent is to provide as much data and as many known correlations as possible to the machine learning system.
ACFT Process: Convert Motion to a Human Digital Twin
Deadlift (male)
Green indicates “The way this subject performed the task, the ACFT event required <70% of the peak torque required to perform the CST at that joint.”
Data for 2 ACFT tasks: deadlift and hand release pushups are provided for 1 male and 1 female subject.
Manufacturing Assembly HF Assessment
- Human Systems Integration
- Human Performance
- Product Design, Development and Testing
Santos has Biomechanics & Physiology
US Marines: SoldierSim – Load and Task Execution
Marine Corps Times recently recognized the major contributions made by the Virtual Soldier Research Project (VSR) at the UI Center for Computer-Aided Design (CCAD) to create SoldierSim™, a Warfighter simulator. SoldierSim™ is a biomechanics and physiology simulation tool for burden management that resulted from a five-year, $8.6 million project awarded to VSR by the U.S. Office of Naval Research and called Enhanced Technologies for Optimization of Warfighter Load (ETOWL), and transitioned to its final client, the Marine Expeditionary Rifle Squad (MERS). The purpose of the recently completed SoldierSim™ project is to create simulation tools for the study of load carriage by military personnel.
For example, military commanders using SoldierSim™ can conduct trade-off analyses of load carriage in terms of agility, survivability, human performance, and physiological assessments by programming Santos® with specific height and weight data for each person, loading Santos® with gear selected from a menu of some 160 Marine specific 3D representations of gear, and having Santos perform various warfighting scenarios. Depending upon the stress experienced for each task, Santos®’s spine, knees, ankles, and other joints will flash either green for low stress, yellow for moderate stress, or red for high stress. According to the Marines, using a 3-D computer-aided design capability allows gear developers to outfit and change a Marine avatar any way they can imagine before running it through a virtual obstacle course. SoldierSim™ is part of the Warfighter Simulation initiatives
An acquisition tool
Let SANTOS and SOPHIA do the testing for you
- Mobility
- Survivability
- Lethality
- Human performance
- Weight: 7.9 lb (3.6 kg) empty 9.8 lb (4.4 kg) loaded
- Effective firing range: 600 m (point target); 700 m (area target)
- Maximum firing range: 3,938 yd (3,601 m)
- In service: 2010–present
- Rate of fire: Sustained: 36 rpm; Cyclic: 700 to 900 rpm
- Barrel length: 16.5 in (420 mm)
- Length: 36.9 to 33 in (940 to 840 mm) w/ adjustable stock
- Feed system: 30-round STANAG magazine
Soldier lethality and survivability, is a complex assessment of the interplay between soldier physical performamce, materiel effectiveness (i.e, effectiveness of enabling technologies to provide protection, lethality, mobility, information, communication, and concealment), squad assignments and responsibilities, mission planning, and threat assessment, while considering any degradation of performance and operational effectiveness due to injury of one or more soldiers. SQUAD OVERMATCH addresses the need for capabilities to effectively evaluate trade-offs among these considerations both to maximize the probability of mission success and maximize solider survivability/operational effectiveness is paramount to mission planning. The SQUAD OVERMATCH simulation environment constitutes a capability for simulating a Squad scenario, with personnel equipment distributed among squad members, evaluating squad performance, and ultimately informin requirement, procurement evaluation, and optimizing Squad performance.
SQUAD OVERMATCH scientifically addresses soldier mobility, lethality, load, squad, and Soldier performance, implemented as a single system operating with interdependent variables, including equipment load, anthropometry (body variation), scenarios, terrain, friendly and enemy forces. The system enables modular development and inclusion of metrics as output, including mission effectiveness, time to completion, squad performance, and casualty assessment developed in collaboration with the Army Future Command DAC, USARIEM and other partners.
An acquisition tool
- Task analysis
- Safety
- Performance
- speed
- time
- fatigue
- energy
Warrior Performance
- Effects of Load
- Effects of gravity
- Muscle fatigue
- Muscle fatigue
- Clothing restrictions
- Terrain
- Energy expenditure
TRAINING DATA
Player Profile
- Age
- Gender
- Weight
- No of games
Body Parameters
- Modifiable
- Physiological
- Physiological tracking and readiness
- Strength
- Non-modifiable Anthropometry
Daily Measures
- Physiology
- Training Load
- Player Load ( Distance, Total IMA, Player Load/Minute, IMAs)
- RPE Load
- Time dependent
- Wellness questionnaires
- Nutrition, Stress
- Academic Intensity, Sleep Quality , Sleep Duration, Fatigue
Injuries
- Injury history
- MSK
- Self reported to ATC & physician
- Injury Data (MSK, Type, Date, location, type, grade)
Risk Factors /Proxies
- Valgus angle
- Past injuries
Dynamics
- Biomechanics metrics
- Kinetics
- Kinematics
- Energy
- Accelerations
- Peak-avg reaction forces
- Peak- avg torques at joints
- Time to completion
Subject
- Age, weight
- Gender
- Weight
- Strength
- Flexibility
- Physiology
- Expected
- Training Load
- Past injuries
- FMS
- Proxies
Propensity for Injury
- Propensity for Injury
- Physiological performance
- Biomechanical
- performance
- Fatigue
- Time to failure
i predict
MALUM TERMINUS is a simulation platform for Musculoskeletal Injury avoidance and prevention with an ultimate objective to enhance Warfighter performance by maximizing the training load and providing customized strength and conditioning interventions for the individual Warfighter. The simulation platform will also serve as an open environment for researchers to import injury data and models into the human simulation. Building upon the SANTOS® human simulation environment, MALUM will create a virtual avatar of an individual Warfighter by taking in various physical, physiological, and biomechanical parameters. A user will then be able to prescribe high intensity tasks to the virtual Warfighter. The software will then simulate the Warfighter and use data available from other commercially available human monitoring systems to predict jury risk to the Warfighter in performing these tasks.
Injury Mitigation
Understanding causality of Injury
An important aspect of our development is the temporal tracking of data and its effect on predictions. Sleep, for example, 2 nights before may have more of an influence on an athlete than stress on the same day. The predictive network takes into consideration the time and relation between all these parameters.
Armor and Personal Protective Equipment (PPE) Assessment
- Hit detection
- Internal organs (hit)
- Inertia (task based)
- Weight and CG
- Range of motion (restriction)
- Mobility/agility
- Balance and stability
- Torque
- Sizing and proper fit (somewhat)
- Bulk
- Head protection (helmet)
- Workspace (how an armored Warfighter fits elsewhere)
Not included
- Fit and comfort (e.g. chafing)
- Soft armor
- Skin based restrictions
- Casualty assessment (ORCA)
- Armor penetration mechanics
assessment of flexible armor for the special ops
- Mobility Index
- Weight
- Stability
- Potential Energy
The University of Iowa Virtual Soldier Research (VSR) program was asked to independently conduct an evaluation of soft armor vests, manufactured by HARDWIRE to determine the amount of twist (torsional angle) as worn by a Soldier in maximum and/or extraneous movements. The VSR team has significant experience working with the US Military and with armor design companies.
As part of this study, the amount of twist (torsional) deformation of the soft armor on a Warfighter body undergoing extreme range of motion tasks was quantified using three different approaches: (a) optical, (b) numerical, and (c) finite element analysis. This torsional deformation was then compared with the torsional deformation of the soft armor achieved on a test machine provided by Hardwire, LLC, and that subjects the armor to a cyclical torsional fatigue. In each test, the results show that the deformation of the vest on the machine is substantially higher than the deformation of the soft armor achieved in extreme motion cases when it is worn by the Warfighter. The VSR team concludes that the test of subjecting this soft armor material to such large torsional deformations by the machine (at +/- 60 degrees) is inconsistent with any type of motion exerted by a Soldier.
In order to arrive at these quantitative results, a markerless motion capture suite was used to capture full body human motion, a marker based motion capture system was used to capture the motion of various points of interest on the armor vest, and full analysis was done using Matlab and C++ code. In addition, a simple finite analysis model was created to inform on the high stresses produced in the armor while subjected to the torsional (twist) in the provided machine.
Task Analysis
