Description:
OBJECTIVE: Develop a software simulation tool that models the external force/torque inputs and risk of injury to the musculoskeletal system of soldiers carrying loads with and without assistance from body-wearable robotic devices. DESCRIPTION: Soldiers, Marines, Sailors, and Airmen on foot and engaged in field training or combat operations often carry heavy loads (35-65 kg or more) consisting of basic clothing and individual equipment and added mission-specific gear (1, 2). Missions are often in harsh environments and can last from hours to weeks. Limited opportunities for resupply drive soldiers to carry everything needed for the mission. Carrying heavy loads increases metabolic energy expenditures, degrades gross- and fine-motor physical performance, and results in significant pain and discomfort, as well as musculoskeletal injury (2, 3). Notably, musculoskeletal injury rates have increased six-fold since the 1980s, with the rate of injury in women outpacing that of men. The majority of musculoskeletal injuries are associated with overuse (3), with excessive load carriage recognized as a contributing factor (1,2). However, comprehensive scientific understanding of the impact of load carriage on physical performance and risk of musculoskeletal injury just emerging (4). PHASE I: Task 1: Provide a detailed plan and software architecture needed to develop a simulation tool that would enable the effect of load carriage on joint and muscle loading to be examined. Determine if there is sufficient information available in the open scientific literature to be able to accurately describe the load-carriage related physical constraints of, and force and torque inputs to the human musculoskeletal system. Task 2: Identify candidate body-wearable robotic assistive device(s) for analysis. Identify primary and secondary muscle groups most likely to be affected during device use. Task 3: Provide a detailed development plan for a simulation tool that accurately models the physical constraints and force/torque inputs to the human musculoskeletal system associated with normal load carriage activities performed while using one or more of the identified body-worn robotic assistive devices. This simulation tool should ultimately enable the user to quantify the overall effect of the use of assistive devices on agility, metabolic costs, load carriage performance, and risk of musculoskeletal injury. Develop the study plans required to develop and validate the simulation. No testing with human test volunteers will be needed in Phase I. PHASE II: TASK 4: Create a simulation tool that would enable the effect of load carriage on joint and muscle loading to be examined with or without one or more of the body-wearable devices identified in Task 2, using, for example, a musculoskeletal simulator such as OPENSIM or SIMM (6). Define constraints that would be imposed by the assistive device(s) on human motion, accurately reflecting the mechanical compliance, both rigidity and flexibility, of the body-wearable device(s). Define actuation inputs to the body-wearable device(s). Create a model of canonical task(s) of interest, such as lifting, running, and throwing. Develop scripting methods for performing Monte Carlo simulations of both nominal and off-nominal use cases. TASK 5: Conduct Monte Carlo simulations of both nominal and off-nominal use cases of the body-wearable device(s) for identified canonical tasks, for a range of muscle activation rates (e.g. slow vs. explosive motions). Simulation parameter boundary conditions would be drawn from literature, or from Government-provided human subject data (if available). TASK 6: Extract individual muscle forces and excitation patterns from simulation output. Analyze statistics of individual muscle forces to measure peak and Root-mean-square (RMS) force output, power output, and other metrics of interest. Using outputs from the simulations and information from the open scientific literature, cross-compare performance enhancement available from body-wearable devices, and compare to unassisted performance. Determine if individual joints or muscles are subject to excessive peak or RMS loads. Evaluate overall effect of device use on agility, metabolic cost, and load carriage performance, and risk of musculoskeletal injury. Task 7: Deliver a prototype simulation tool suitable for test, validation, and use by Government subject matter experts to examine the effect of normal load carriage activities on joint and muscle loading and risk of acute and chronic injury with or without assistive devices. Testing with human test volunteers may be needed in Phase II to validate the simulation. PHASE III: The envisioned end state of this research and development effort is a commercial-grade simulation and analysis product suitable for use in industrial situations where new jobs are being established and/or the use of new equipment, including personal robotic assistive devices, is being considered. This product would also be of great use as the body-worn robotic assistive devices transition from Military and Industrial settings into Medical and Rehabilitative settings. The ability to simulate the impact of new jobs and new equipment on musculoskeletal performance and the potential for injury would benefit the Government oversight groups such as National Institute for Occupational Safety and Health (NIOSH) and industry by ensuring safe and efficient work environments. Furthermore, the ability to perform initial evaluations of proposed robotic assistive devices in a timely manner without the need for costly and time consuming experimentation with human test volunteers would be beneficial. REFERENCES: 1. Load Carriage in Military Operations: A Review of Historical, Physiological, Biomechanical and Medical Aspects (2010) Joseph Knapik, ScD, and Katy Reynolds, MD; in: Borden Institute Monograph Series edited by W.R. Santee, PhD and K.E. Friedl, PhD, Colonel, US Army (http://www.usariem.army.mil/Pages/downloads.htm, accessed 20 Sept 2012) 2. Weight of War: Gear that protects troops also injures them. Hal Bernton http://seattletimes.com/html/nationworld/2014209155_weightofwar06.html (accessed 20 Sept 2012). 3. Bell NS, Schwartz CE, Harford TC, Hollander IE, Amoroso PJ. Temporal changes in the nature of disability: U.S. Army soldiers discharged with disability, 1981-2005. Disabil Health J. 2008 Jul;1(3):163-71. 4. Abdel-Malek, K., et al. A physics-based digital human model. Int. J. of Vehicle Design Issue Vol. 51 (No. 3-4), 2009, pp. 324-340 5. Lee, H. et al. The Technical Trend of the Exoskeleton Robot System for Human Power Assistance. Int. J. Precision Eng. And Manufacturing. 13(8): 1491-1497, 2012. (http://link.springer.com/content/pdf/10.1007%2Fs12541-012-0197-x) 6. OpenSimulator (OPENSIM) (accessed 20 December 2012): (http://opensimulator.org) and Software for Interactive Musculoskeletal Modeling (SIMM), Musculographics Inc., (http://www.musculographics.com/html/products/SIMM.html)
