Tag Archive for: Predictive Digital Human Model

Santos Lite Software Updates

In August 2021, SantosHuman, Inc. completed several updates to Santos Lite, our foundational digital human modeling software suite. The modifications include new avatars for Asian males, elderly females, and other human body types as well as trade-off analysis fixes and improvements and motion capture visualizer updates.

To learn more about the Santos Lite software updates, improvements, and bug fixes, download the complete change log dated August 31, 2021.

SantosLite Software ChangeLog-Ver0_0_2021_0831

If you have other questions about Santos Lite or Santos Pro, see the Santos FAQ page.


Q&A with the CEO: Why was Santos® created?

In this month’s Q&A, Steve Beck, CEO of SantosHuman Inc., addresses the question of why Santos was created.

Q: Why was Santos® created?

Santos® exists because Trial & Error is a terrible approach to design.

To unpack this a bit and make sure we’re all thinking about the same thing, let’s look at how Trial & Error is used in a cottage industry. Our example begins with an artisan, alone in a workshop, diligently giving physical form to some radical new wooden chair design. It’s complex enough to require several weeks to complete but as soon as the glue dries, our artisan sits down to reflect on a job well done. This is the Trial part in the scenario and while the chair’s aesthetics are impressive, it falls apart almost immediately. And that’s the Error part. Having completed the 1st Trial & Error iteration, the artisan must now work to address the flaws in the design through a series of subsequent iterations.

For products where materials are cheap, production is simple, and function is not critical, design by Trial & Error is often the only viable option. But imagine using that approach to design a high-rise apartment building where structural integrity could not be determined until full occupancy on a windy day. Or, to design an aircraft where aerodynamic properties could not be determined until after take-off. Or, to design a high-speed passenger train where nobody knows if the suspension systems will withstand the forces involved in a fast, twisty trip through a mountain range.

Trial & Error in these cases would be unthinkable. Further, it would be impossible to have ever developed today’s exceptionally high-quality products with their amazing capabilities using Trial & Error. Yet, products with amazing capabilities do exist, and they are of exceptionally high quality, so how is this accomplished?

Predictive Models for Virtual Testing

The quality and capabilities available in products today are achieved through the use of mathematical models that can virtually test properties critical to the design including structural integrity, aerodynamics, and how well mechanical systems perform during operation.

How does that work?

Let’s continue with our chair design example, but instead of expending the time and materials required to test and refine a series of complete chairs, a mathematical model is used to predict structural integrity for a virtual version of the chair, relative to a range of occupant weights. Upon completion, the virtual tests provide insight as to where the chair’s structure is sound versus where it may fail. Armed with this insight, our artisan modifies the virtual chair design to address the weak areas, runs additional virtual tests to confirm the solution, and then moves quickly into production without ever having to create a single physical prototype.

While obviously a superior approach to guessing and hoping for the best (a.k.a. Trial & Error), the above scenario is not likely to fit within a cottage industry business model. The cost of the technology required to use predictive models as described would be far beyond the means of a typical artisan. But for products where materials are expensive, production is complicated, and function is critical, Trial & Error is avoided wherever predictive models exist. Why? Because predictive models provide critical insight early in a product’s design cycle. And why is that important?


The ability to gain insight early in a design cycle is important because the earlier the need for change is detected, the less costly those changes are to make. And it’s not just a little bit cheaper. This is a well-studied relationship where change becomes significantly more expensive the closer a product gets to production. Post-production, the cost of change can be staggering.



This is why predictive models are so valuable and have been so widely adopted. Predictive models provide critical insight at the earliest stages of design, leading to better designs that can be brought into production sooner, which significantly benefits the bottom line of nearly every company, in every industry.

What does this have to do with Santos?

As valuable as these widely adopted models are, none of them have the ability to predict whether humans can interact with products or processes effectively and safely. And, because there has never been a way to predict the Human-in-the-Loop, all industries have had to rely on Trial & Error for human-centric design. One of the many unfortunate results of this is that the United States Department of Defense (US DoD) is often required to address usability issues after systems have already been delivered; when options to address design issues are most limited and also most expensive to implement.


Santos: The Alternative to Trial & Error

With all of that in mind, let’s return to the question. Why was Santos® created?

Santos was created to eliminate Trial & Error from human-centric design. The genesis story begins in the early 2000’s when the Tank Automotive Command Center (TACOM) was considering the development of the next generation tank. History suggested it could take as long as 13 years for a new tank design to evolve from whitepaper to production. Over those 13 years, 9 physical prototypes could be required at an estimated cost of $1B (USD) each. One of the primary reasons $9B worth of physical prototypes could be required would be to ensure critical Warfighter-in-the-Loop issues are understood and addressed because failure to do so will cost lives.

TACOM understood it was relying on the same Trial & Error approach to design that an artisan chair maker uses. But instead of evaluating a wooden chair, Trial & Error would be used to develop and refine an entire tank in order to make sure warfighters are able to operate its sophisticated systems safely and effectively. Each iteration was going to cost US Taxpayers $1B and TACOM wanted a more objective and cost-effective approach. They wanted to virtually test for Warfighter-centric issues in the same way that Finite Element Analysis (FEA) is used to virtually test for structural integrity issues, or the way Computational Fluid Dynamics (CFD) is used to virtually test for aerodynamic issues, or the way Multi-Body Dynamics (MBD) is used to virtually test for mechanical system operation issues.  Those predictive models significantly reduce the need for physical prototypes. TACOM wanted to do the same thing for Warfighter-centric design.

That’s the problem we were asked to solve in 2003.

And we did it. We solved the problem. The research conducted in pursuit of this solution resulted in what is now commonly referred to as Santos®. Santos technologies include the ability to predict human physical behavior and performance so that Warfighter-in-the-Loop issues can be identified and addressed at the earliest stages of design. Now, instead of expending massive resources at the end of a design cycle to test system usability in a reactive role when options for change are most limited and most expensive, Santos® allows design teams to perform Warfighter-centric system evaluations in a proactive role, at the earliest stages of design. This can only be done with a predictive human model.

Santos® Means No More Trial & Error in Human-Centric Design

If you’re interested in seeing a quick example deployment of this technology, click on the image below to go directly to a previously posted blog that includes a video demonstration. Or, feel free to contact us directly at Sales@SantosHumanInc.com.

Thanks for tuning in and, as always, let us know what you think.  We’d love to hear from you.


– S

New Work-In-Progress Video: Predicting the Effect of Restraint Systems on the HITL

The ability to place restraint systems on the human-in-the-loop (HITL) has been available in Santos Pro’s predictive human model since 2014, but it was a proof-of-concept that was not fully developed. Now, we’re working on this capability and want to show you our progress.

A client needs this solution for a project requirement, so we’re working to make this everything it should be. The advancements in our predictive human models are making this easier than it was five years ago to improve the addition of restraints. The idea is to make it so you can predict the effect of restraint systems on the HITL more easily using Santos Pro, which is a highly advanced, always-evolving digital human modeling program.

Please watch this video and let us know your thoughts about how you might apply this capability, which will be available soon.

And, in case you missed it, be sure to check out our other featured videos on YouTube.

– Steve Beck

New Work-In-Progress Videos: Supporting Human-Machine Teaming

Work-In-Progress Video 001: Supporting the Development & Evaluation of Human-Machine Teaming Systems

It seems like we’re always working on something we’re excited about. But, once the capability exists and we’ve moved on to refinement mode, we’ve already set our sights on the next thing. That’s the problem with goals—you focus on them while they seem difficult or impossible to achieve, but as soon as you’ve done the hard work to make them attainable, you move on to the next challenge. Unfortunately, this often occurs without even noticing that you’ve accomplished something you weren’t even sure you could achieve when you started.

That’s just human nature. We all do it. But, for SantosHuman Inc., I need to do better. I need to make sure we highlight the achievements along the way.  With that in mind, we’re going to start letting you in on the things we’re working on—while we’re all still excited about working on them.

This first installment of the Work-In-Progress series demonstrates a capability goal we’ve been working towards for a very long time.  The ability to use Santos technologies in the development and evaluation of human-machine teaming (collaboration robotics, human-agent teaming systems, etc.) will very soon be available within our flagship product, Santos® Pro.

Take a look and let us know what you think.  We’d love to hear from you.

-Steve Beck

Video Demo: Support for Motion Capture

The predictive nature of Santos technology means we don’t require motion capture to evaluate human systems integration requirements. However, many of our clients had expressed a desire to use motion capture, and we initially provided this capability in Santos Pro in 2013.  While the capability was refined in 2014 to include the fingers, we noticed we had never provided a video tutorial.

In this new video tutorial, we’ve added voiceover narration to further enhance the demonstration of these motion capture capabilities. The voiceover tutorial begins at 1:45 into the video so make sure you have your sound turned on.


To learn more about using Santos Pro, view these video and FAQ resources:

Learn more about Santos Pro on our Products page.

Q&A with the CEO: What are the benefits of using Santos®?

This month’s Q&A with Steve Beck, CEO of SantosHuman Inc., addresses the benefits of Santos® to your company.

Q: What are the benefits of using Santos® technologies?

A: Let’s look at this question from 3 different perspectives, all in terms of reducing costs.  We’ll start with the U.S. Government because, frankly, SHI wouldn’t exist without them.  Then we’ll look at Private Industry and finally from the perspective of Safety.

U.S. Government

The original funding for what is now commonly referred to as Santos came from the U.S. Army Tank-Automotive & Armaments Command (TACOM) in 2003.  TACOM program managers explained their motivation for this program in the following way. They told us that the next generation tank would take approximately 13 years to go from white paper to production. Historically, within those 13 years, 9 physical prototypes would be required. Each of those physical prototypes would cost approximately $1B (2003) and 90% of that cost (funded by US Taxpayers) would be committed as soon as the contract to build the prototype was awarded. They also said that one of the critical reasons for creating these physical prototypes was to make sure Warfighter-in-the-Loop issues are understood and addressed prior to production because getting those wrong would cost lives.

Their initial assumption had been that an existing commercial, off-the-shelf (COTS) digital human model (DHM) could be deployed early enough within design cycles to reduce the number of physical prototypes required. This would reduce the cost of, not just next generation tanks, but any new system and allow better designs to be brought into production sooner. However, upon completing a survey of the COTS DHM options available, they determined none of them could be used to achieve this goal. What they said they needed was a way to predict what the Warfighter would do and the program funding, therefore, was a catalyst for DHM research that could lead to capabilities more closely aligned with US DoD DHM requirements.

In the world of Defense Contracting, Santos represents a Warfighter-Centric alternative to the traditional Trial & Error approach to system design that can save billions in taxpayer expenditures.

Private Industry

Many years ago, I had asked our contacts at one of the world’s largest automobile manufacturers what Santos technologies meant to their industry. Based on data from over 100 years of designing and manufacturing automobiles, they said every new vehicle design historically comes with about 5000 problems. Any of those problems that can be addressed prior to production represents a savings of about $50,000. And in the year this conversation took place, they indicated 9 new vehicles would be going into production.

Those numbers suggest $2.25B worth of cost savings if 100% of the issues could be addressed prior to production.  However, they also indicated that not all of those issues are human-centric. Paint, for example, might not cure correctly or hoses may not fit or door assembly mount points may be misaligned. While those are obviously not human-centric issues, they said anywhere between 10% and 20% of those 5000 issues are human-centric.

If you run those numbers and divide by 9 new vehicles, Santos represents savings of between $25M and $50M per new product for one company in a single year because Santos predictive models provide a unique ability to inform and support human-centric design decisions at the earliest stages of product development.


US companies spend between $50B and $70B per year on work-related injuries. In addition, our contacts within the U.S. DoD have said that the greatest source of lost days for Warfighters is due to equipment use. With that in mind, consider that an extensive study by two World-renowned ergonomists shows that commonly used tools to assess exposure to work-related risk of injury can be off by as much as 16 lbs. This means that even though your company may be assessing tasks for risk of injury, there’s a pretty good chance task risk is being under- or over-estimated.

Manufacturing analysisUnderestimating risk means exposing your workers to increased risk of injury and this is critical for 2 reasons. Not only does it impact the lives of your employees, cost of injury calculators indicate that a single back injury with a $100K payout can have a ripple effect throughout a company requiring an additional $4.2M in sales to offset the cost of just that one injury.

Overestimating risk means expensively and needlessly redesigning tasks that could safely be accomplished as originally designed. Either way, these costs significantly affect the bottom line of just about every company in every industry.  And this is why Santos technologies include the world’s most accurate and most extensively validated method of predicting exposure to risk of injury available today. Use this link if interested in finding out more.

Back to the original question.  What are the benefits of using Santos?  A better question might be, what does it cost to NOT use Santos?

Thanks for tuning in.  You can learn more about other Santos capabilities here and, as always, let us know what you think. We’d love to hear from you.

– S

Video Demo: Integrating Santos into Other Applications

Could a Santos model be added to your product? This video demo shows how the Santos Basic Predictive Model for Physical Behavior, or BPMPB, Software Development Kit (SDK) integrates into existing applications. The Santos BPMPB SDK offers flexibility when integrating into other software environments.

So, if you’re wondering if Santos technology is portable, please watch this video to learn more. It could save your design team even more time during the early stages of product design.


Learn more about the Santos BPMPB SDK on our products page.

The Expense of Not Optimizing the HITL: Predictive Models for Precision Grasps

In a previous blog series (post #1 of which can be found here), I had said that traditional design processes do not include human-in-the-loop (HITL) evaluations until so late in a product’s development cycle that change is no longer a realistic option.  While that series focused on just four examples, each from a different industry, SantosHuman Inc. (SHI) works with clients from many industries and the anecdotal evidence for that statement is overwhelming.

Blog series posted.  Next topic.  Moving on.

Or at least, I thought so until a recent client engagement provided an example so perfectly suited to that series that I found myself agitated that it wasn’t included.  This post alleviates that agitation and, going forward, similar posts could serve as addendums to that series.  However, these addendum posts would be used sparingly and only for the most relevant examples because our experience at SHI indicates examples will continue to be plentiful.

Santos precision graspIn this first addendum entry, a global manufacturer in a highly competitive industry redesigned the thumb-operated switchgear on a new product scheduled to be in production soon. They told us their usual approach to evaluating something like this requires a working physical prototype and can take between two and three months to complete. Early on they were notified that a prototype would not be available prior to production so their plan had been to perform the study as soon as the vehicle was in production.  The problem was that the company expected to be producing thousands of these vehicles every day when launched.

Let’s review that last paragraph just in case one of your eyebrows isn’t now several centimeters higher than the other. If the evaluations of the newly designed switchgear were to proceed as originally planned, tens of thousands of their products would be in dealerships and in the hands of new owners by the time the evaluations were complete. As you can imagine, the thought of having to address usability issues for tens of thousands of vehicles, coupled with the loss of market share that accompanies poor operator feedback in a highly competitive market, was causing considerable concern.

Santos thumb switchThey contacted us hoping there might be some way to use just the CAD geometry to perform the switchgear usability evaluations prior to launch.

Once again, we see that traditional and pervasive approaches to product design not only value capability over usability, existing processes make it impossible to even consider usability until it’s too late to do anything about it.

The good news?  As a result of development efforts SHI undertook in 2014 to respond to the needs of one of the world’s largest consumer goods manufacturers (which you can read more about here*), Santos® capabilities include the ability to predict precision and power grasps.  As with all Santos® predictive models, this is a 1st principles approach to predicting grasps that not only affects – and is affected by – the entire body, it can simultaneously take into consideration other competing operator task requirements.

Our clients aren’t interested in replicating what they can already do with the virtual mannequins that have been around for decades.  SantosHuman Inc.’s clients are looking for solutions to problems that would be impossible to solve without us.

Take a look at this unique capability demonstrated in an example use case and then let us know what you think.  We’d love to hear from you.

– S

Q&A with the CEO: What problem is Santos® meant to solve?

This month’s Q&A with Steve Beck, President & CEO of SantosHuman Inc. answers the question of what problems Santos is designed to solve.

Q: What problems are solved by Santos®?

Santos technologies provide a platform that enables our clients to look at humans-in-the-loop in a wide variety of applications. Our capabilities stand out as solutions to not one—but two—of the most persistent problems in product design.

  1. wheelchair analysisDesigning for Humans Earlier in the Process. The Santos first-principles approach to predicting physical human behavior and performance allows human-in-the-loop criteria to be considered at the earliest stages of product development. This enables our defense and private industry clients to design for increased performance and increased customer satisfaction from the start resulting in better designs that can be brought into production sooner. If you haven’t seen the recent blog series on this topic, you can find the first post in that series here.
  2. Predicting Exposure to Risk of Injury. A 12-year study by two world-renown ergonomics researchers involving thousands of subjects indicates that commonly used tools for assessing work-related exposure to risk of injury are not only inaccurate but can be off by as much as 16 lbs. Putting that into perspective relative to the lives of the workers your company employs, assume a task assessment underestimates the load a worker must handle by 16 lbs and your company has been given a green light on that task, which could be as much as 16 lbs. heavier than should be allowed. This means your workers could be performing a task all day, every day, that exposes them to a significant increase in risk of injury. With all of that in mind, consider that a) work-related injuries cost U.S. companies an estimated $50 to $70 billion per year and b) our defense clients have noted that U.S. warfighters lose the most days due to injuries associated with equipment use.lift analysis in Santos Pro

Let’s now assume a task assessment overestimates the load a worker must handle by 16 lbs and your company has been given a red light on that task, which could be performed with minimal exposure to risk of injury as originally designed.  When was the last time you saw a budget line item for unnecessary and expensive task redesign expenditures?

Whether you’re underestimating the loads your workforce can handle and exposing them to increased risk of injury -or- expensively and needlessly redesigning their tasks, relying on commonly and widely used tools for these types of assessments, most of which have been shown to be off by as much as 16 lbs., affects the bottom line of just about every company in every industry.

We worked closely with Professors Jim Potvin, Ph.D., and Nick la Delfa, Ph.D. to provide their solution – the most accurate and extensively validated method of predicting exposure to risk of injury for manual material handling tasks available today – within Santos products through the Arm Force Field Plug-In,

Learn more about other Santos capabilities and, as always, let us know what you think.  We’d love to hear from you.

– S

Video Demo: What’s the Difference Between a Predictive Human Model and a Traditional Digital Human?

As you might expect, I spend a lot of my time talking to people about Santos® technologies.  When they are familiar with digital human modeling at all, they’ll often say things like, “Digital human models have been around for decades.  Our teams have tried them but feel they’re difficult to use and ultimately not that much of a value-add.  Why should we be interested in yours?

For those of us who have been involved from the very beginning in what is now commonly referred to as Santos®, the answer is obvious.  But, simply saying, “Santos provides the ability to predict human physical behavior and performance“, isn’t meaningful before also providing a great deal of additional background information.  This blog post attempts to make one of the many significant values of this unique capability a bit more obvious.

The video linked to below provides a side-by-side comparison highlighting the difference between using a truly predictive human model (on the left) versus the way in which a more traditional digital mannequin is used (on the right).  While Santos® predictive models provide significant advantages for human-centric design and evaluation in any industry, this video focuses on a contrived cab space development application.

How to Watch the Video
Both the left and right sides of the video were created using a single digital human character within our flagship product, Santos Pro.  The right side of the video mimics the traditional way in which digital human models were designed to be used.  The left side demonstrates the use of Santos predictive models.

The right side of the video only needs to be watched once through the first iteration.  There’s a lot happening on the right side of the video at first so it’s not only initially more interesting, it’s almost impossible not to watch.  In comparison, the activities on the left side are rather boring at first as the user is just setting up the constraints required to define an operator task.  So go ahead and focus on the right side through the first iteration.  The activities shown on the left will complete at about the same point in the video as the 1st iteration of the activities on the right so you’re not going to miss anything.  Note, however, that the two sides only complete at about the same time because the right side has been sped up by about 5x and that’s an important point.  It takes less than a minute to set up the predictive model task on the left but takes about 5 minutes for a highly experienced, expert user to manually rotate individual joints into position on the right.

After the first iteration of activities on the right is complete, that clip just repeats over and over until the end.  But you’ll find you don’t have to watch the right side very long to see that manually rotating digital mannequin joints is non-intuitive, time-consuming, and tedious.   In addition, it is clearly a highly subjective process where compromised, even non-human-looking, results are a frequent option.  And as if that wouldn’t be frustrating enough, consider there are no economies of scale to using a digital mannequin.  Every design option explored requires another round of subjective and tedious manual joint rotations.  And then, after all that effort, when you’re all done, what is it you actually know?  It’s no surprise that many design teams consider the use of digital human mannequins an obstacle as opposed to a solution that can be used to bring better, customer-focused designs into production sooner.

In contrast, use of a truly predictive human model (the left side of the video) allows multiple and even competing task objectives to be evaluated in a system-of-systems approach that, in this example, includes seat location, steering wheel and pedal use, and even a vision requirement. The advanced predictive nature of Santos enables your teams to identify Human-in-the-Loop requirements at the earliest stages of product development while change is still a cost-effective option.

SantosHuman Inc.  When getting it wrong is not in the budget.

Take a look and let us know what you think.  We’d love to hear from you.

Santos® Pro provides a foundational platform for truly human-centric design through a full range of predictive human modeling capabilities. Learn more about our complete product line.