BIOFEST INVEST APPLICANT

T4 Movement

Company Contact:

Legal Entity Type: LLC

Company Type: Medical Device

Company Stage: Feasibility

No. of Employees: 1

Desired Financial Amount: $250k for project activation

Background

Company Background

T4 Movement, LLC was established in May of 2021 by founder and CEO Tony Treser. T4 Movement’s motivation stems from the Tony’s personal journey suffering from chronic back and eventually overcoming the issue. Tony has extensive first-hand experience intensely pursuing a comprehensive variety of existing treatment options for back pain. In his case, the key to overcoming the chronic back pain began with an objective personalized biomechanical evaluation. Personalized biomechanical evaluations help patients with musculoskeletal disorders identify the root cause of their issue and effectively guide rehabilitation. It is our company’s mission to empower patients with back pain and musculoskeletal injury through actionable biomechanical evaluations. Since the company formation, Tony has recruited three engineers that are currently working on T4 Movement project work part-time. T4 Movement also has established advisors from relevant sectors such as Healthcare IT, Data Science, and Clinical Treatment. The technology origins of our innovation have been developed by our research institute partner, Southwest Research Institute (SwRI), over the past several years. SwRI’s markerless motion capture technology is ready to move from a laboratory setting into the clinical field.

Management

Tony Treser – CEO -Machine Vision Product Development, Technical Sales Engineering, Building Strategic Relationships, Engineering Creative Technical Solutions, and Leading Cross-Functional Teams to Manage Complex Projects in Demanding Environments Emmanuel Oluga – CTO -Computer Engineering, Electrical Engineering, Deep Learning, Data Analytics, Medical Device Development Nayab Ali – COO -Data Analysis, Data Compliance in Life Sciences, Event Coordination, Business Management Ashley Larweck – CIO – AutoCAD, SolidWorks, Java, Computed Tomography, MRI, MATLAB, C, AI/VR ————— PARTNERS: Southwest Research Institute (Technical Partner) – Markerless Motion Caputure Technology RunLab (Clinical Partner) – Biomechanics based Physical Therapy Treatment Clinic

Board of directors

Zac Bujnoch – Business Development -Healthcare IT, Economic Development, IoT, Technical Consulting Gabe Lozano – Data Science -CEO of ‘Decide Technologies Inc.’ a machine-driven automated decision maker for online advertising -https://decide.co/ Dr. Christopher Hughes – Biomechanics Advisor -PT, PhD, OCS, CSCS -Instructor at Slippery Rock University

Product / Service

disease area / application

Low Back Pain (LBP) and Musculoskeletal (MSK) Injury | Evaluation, Treatment, and Progression | Sports Medicine, Physical Therapy, Chiropractic

product / Service

Our technical innovation is focused on providing comprehensive and actionable biomechanical evaluations to patients with chronic back pain to improve rehabilitation interventions and outcomes. The innovation consists of three distinct parts: 1. Collecting biomechanical information in a way that is innovative, low-cost, easy-to-execute, and scalable (markerless biomechanical data collection) Patients with low back pain execute dynamic movement patterns (gait, squat, vertical jump, etc.) that are recorded using standard 2D video cameras. The recorded video is processed using machine vision algorithms that generate virtual biomarkers identifying the patient’s body position and joint angles. The coordinates provided by these biomarkers are filtered through biomechanical analysis equations that calculate and record the patient’s kinematic and kinetic information. This method of biomechanical data collection saves enormous amounts time and money, making it a realistic option for healthcare providers to provide this type of evaluation service. Today, this type of analysis must be conducted using 3D IMU sensors and force plate technology. This technology costs upwards of $50,000 for equipment and installation, making it an unrealistic option for healthcare providers to purchase. We believe we could provide this technology for less than $10,000. By being markerless (no sensors need to be attached to patient), valuable setup and tear-down is saved during the evaluation (upwards of 15 minutes time saved per evaluation). Markerless technology also removes the possibility of misplacing the attachable sensors on the patient, making the evaluation easier and more accurate. 2. Automating the data analysis process Clinical input is used to establish healthy parameters to compare against the generated patient data, helping identify movement deficiencies. This provides unique insights into finding the root cause of the patient’s pain and sets the foundation for actionable reporting. The kinematic and kinetic information generated during the collection process is analyzed using machine learning, providing digital reporting that is easy-to-understand and actionable. The findings of the report are communicated to the patient and/or healthcare provider using data architecture and visualization. This report visually identifies and quantitatively defines the movement deficiencies for the patient to address. It also provides corrective action to be taken. Finally, the digital reporting dashboard also tracks the patients progress as follow-up evaluations are repeated. 3. Providing digital reporting that is easy-to-understand and actionable The findings of the report are communicated to the patient and/or healthcare provider using data architecture and visualization. This report visually identifies and quantitatively defines the movement deficiencies for the patient to address. It also provides corrective action to be taken. Finally, the digital reporting dashboard also tracks the patients progress as follow-up evaluations are repeated.

technology / ip

Our technology utilizes neural networking, triangulation, and machine vision. The technology is patented by SwRI for our specific use case. The data analysis and reporting technology is currently being developed as part of our project work. Patents are being developed and filed in parallel.

distribution channels

We intend to initially sell our product and via direct sales for equipment purchase with recurring software subscription fees.

market size

The expected market for our innovation are US healthcare providers that treat patients with back pain musculoskeletal injury. Specifically, our identified customer groups are Sports Medicine Practitioners, Physical Therapists, and Chiropractors. Between these groups, there are a total of over 282,330 established businesses and over 791,000 employed individuals [3-5]. The total market size is over $80 billion annually with an addressable market of over $40 billion. From 2014 to 2019, the number of active physicians in sports medicine increased by 39.8%. This is the largest percentage increase any specialty group except only interventional cardiology (46.8%) (Percent Change Physicians Number U.S. by Specialty 2014-2019). Over 40% of United States Corporate Wellness solutions have increased the priority of ergonomics and musculoskeletal treatment since the COVID-19 pandemic in 2020 (Statista, 2021)

competition

DARI Motion- Strength: end-to-end platform, minimal setup, user-interface, marketing Weakness: cannot do gait analysis, limited to movement modules, too expensive for HCP market, lack big data architecture SiMi – Strength: real-time visual feedback Weakness: Marker-based model, markerless product is >$100k, no kinetic data Theia – Strength: Markerless pose capture, Data visualization Weakness: Lack cross platform security, no kinetic data, lack big data architecture, reporting MAR Systems – Strength: 2-camera system, instant gait feedback Weakness: No help with install, individual structural anatomy not taken into account, limited to only gait — Key Differentiators of T4 Movement: -Personalized patient structural anatomy implementation into our data collection and analysis -Our data evaluation is dynamic and improves with more repetition -Digital modeling for a visual interface reporting framework that is understandable to non-technical users -System is actually affordable

Financials

Desired financial amount

$250k for project activation

previous funding

$8k – Big Rowdy Idea Competition

current financials

Currently, the company is bootstrapping. There is no formal burn rate (no salaries, rent, overhead, etc). $8k from competition winning has been used to purchase raw materials for MVP.

financial use

Short Milestone List: Prototype implementation, data analytics code establishment, software development Extended Overview: 1. The systematic implementation of a new markerless biomechanical data collection technology in a real-world clinical setting: a. The markerless biomechanical data collection technology described above (part 1 of ‘Technology Innovation’) has been prototyped and is ready to be tested in a real-world clinical setting. b. Because backpain is a multidisciplinary issue, we need input from real-world clinicians (potential customers) to determine the following: i. Does the prototype generate accurate data in a real-world setting? ii. Is the prototype easy to use in a real world-setting? iii. How valuable is the protype to your diagnostic and treatment efforts? iv. How does the patient (end-user) feel about incorporating the prototype into their treatment? c. The technical work to be done here will involve partnering with clinicians and physically installing the technology in their facilities. Then working side-by-side with the participating clinicians to improve the protype and prepare for scalable deployment. – 2. Systematic, intensive study directed toward using existing clinical standards as parameters to evaluate large sets of biomechanical data using machine learning a. It will not be realistic to manually analyze the data generated from the markerless biomechanical data collection technology because the datasets will be too large; machine learning must be used. b. The technical work to be done here will involve partnering with clinical authorities that can provide input that will set the foundation for healthy comparative thresholds used to evaluate the data sets. c. The technical work to be done here will involve writing the actual machine learning code for analysis after clinically supported evaluation thresholds are established. d. The technical work to be done here will involve streamlining the flow of data from collection, through the machine learning code, to conclusive results. — 3. A systematic study directed toward translating and applying new knowledge obtained through biomechanical data collection and analysis towards effective patient reporting and rehabilitation. a. The unique biomechanical insights provided from the data collection technology will need to be communicated to the patient and/or healthcare provider after the data analysis is complete. b. The technical work to be done here will include partnering with clinical authorities that can provide input on applying the corrective intervention actions based on the unique insights provided through the data collection and analyzation process. c. The technical work to be done here will involve the design and development of a digital reporting and data visualization interface prototype.

revenue

Our revenue model will be based on equipment purchase revenue + recurring software subscription. Customers will pay for upfront for hardware and pay monthly subscription fee.

exit strategy

We are licensing core technology from SwRI. We will build on top of this to develop a complete product. We will build the company and eventually sell the company once fully developed. This is a 5-7 year effort.

Pitch Video

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