{"id":3983,"date":"2025-05-01T13:46:40","date_gmt":"2025-05-01T13:46:40","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2025\/05\/01\/wandercraft-begins-clinical-trials-for-physical-ai-powered-personal-exoskeleton\/"},"modified":"2025-05-01T13:46:40","modified_gmt":"2025-05-01T13:46:40","slug":"wandercraft-begins-clinical-trials-for-physical-ai-powered-personal-exoskeleton","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2025\/05\/01\/wandercraft-begins-clinical-trials-for-physical-ai-powered-personal-exoskeleton\/","title":{"rendered":"Wandercraft Begins Clinical Trials for Physical AI-Powered Personal Exoskeleton"},"content":{"rendered":"
\n\t\t<\/span> <\/span> <\/span><\/span><\/p>\n

For Nicolas Simon, advancing the field of robotics is a personal mission that could change his siblings\u2019 lives.<\/p>\n

Two-thirds of Simon\u2019s family members use wheelchairs due to mobility challenges related to Charcot-Marie-Tooth disease, an inherited genetic condition. As an engineering student and robotics club chair at France\u2019s \u00c9cole Polytechnique, he saw the opportunity to build a new device that could help his brother and other relatives walk again.<\/p>\n

His robotics startup, Wandercraft, builds mobility solutions for individuals with spinal cord injuries, stroke and other neuromuscular disorders \u2014 with the potential to support the estimated 80 million individuals<\/a> worldwide who require wheelchairs for mobility.<\/p>\n

The company\u2019s Personal Exoskeleton, currently in clinical trials, enables users to stand and walk with the support of AI-powered mechanisms for stability and movement. Users can control the robotic system with a joystick.<\/p>\n

Simon founded the company in 2012 with Matthieu Masselin and Jean-Louis Constanza, whose son also has Charcot-Marie-Tooth disease. The team is accelerating its workflows with NVIDIA technologies \u2014 enabling Wandercraft to harness the latest simulation tools and AI infrastructure to bring new capabilities to its exoskeletons.<\/p>\n

\u201cIt\u2019s essential for the exoskeleton to be fast enough that it can be used in the real world,\u201d said Simon. \u201cBy integrating NVIDIA AI into the device, we can someday enable users to walk at an average pace, cross the road and go up and down stairs.\u201d<\/p>\n<\/p>\n

Advancing Development With Physical AI\u00a0<\/b><\/h2>\n

Wandercraft\u2019s first exoskeleton, called Atalante X, is FDA-cleared and already in use as a neurological rehabilitation tool in over 100 clinical and research settings worldwide, with patients taking over one million steps per month. Approved for use in the European Union in 2019 and in the U.S. in 2022, the device has helped hundreds of patients regain mobility through physiotherapy.<\/p>\n

The startup\u2019s latest device, the Personal Exoskeleton, is aimed at everyday indoor and outdoor use. With clinical trials underway<\/a> in New York and New Jersey, the Personal Exoskeleton integrates AI to continuously adapt to a user\u2019s movements in real time, supporting smooth and stable walking across different surfaces, including concrete, carpet and tile.<\/p>\n

\u201cIt\u2019s very important for us to use physical AI to deliver a better device and a better experience for our users, so they can move through their daily lives smoothly and efficiently,\u201d Simon said.<\/p>\n

\"Woman
Laubach demonstrating the Personal Exoskeleton at NVIDIA GTC. Image credit: Wandercraft<\/figcaption><\/figure>\n

In addition to helping users gain new levels of mobility at home and in their communities, the Personal Exoskeleton could also help reduce the health impacts of being seated all day \u2014 which include increased risk of cardiovascular, skin and digestive conditions.<\/p>\n

Wandercraft is currently experimenting with NVIDIA Isaac Sim<\/a> \u2014 a reference application built on NVIDIA Omniverse<\/a> for simulating and testing AI-driven robotics solutions in physically based virtual environments \u2014 to accelerate its reinforcement learning<\/a> pipeline. The company is also investigating the use of the NVIDIA Isaac for Healthcare<\/a> developer framework for AI healthcare robotics and NVIDIA Jetson Thor<\/a>, an on-robot edge computer built on the NVIDIA Blackwell architecture.<\/p>\n

With these systems for physical AI<\/a> training, simulation and runtime in place, Wandercraft will have a three-computer solution<\/a> for its robotics development.<\/p>\n

\u201cThe technology is there \u2014 you just have to build the device,\u201d Simon said. \u201cWe take all the technology from the field of humanoid robotics, and we apply it to our exoskeleton. So now, the possibilities are endless.\u201d<\/p>\n

At the NVIDIA GTC<\/a> global AI conference in March, Wandercraft demonstrated the prototype Personal Exoskeleton with the help of Caroline Laubach, a spinal stroke survivor and full-time wheelchair user. The exoskeleton system was also featured in last year\u2019s Olympic and Paralympic Torch Relay.<\/p>\n

Wandercraft aims to apply for FDA clearance for its Personal Exoskeleton immediately following completion of its clinical trial<\/a>, with the goal of making it accessible to millions of wheelchair users in the U.S. with expected Medicare coverage<\/a>. The company is currently recruiting additional participants for the clinical trial, which it aims to complete this year.<\/p>\n

\u201cWith this technology, we can enable people to move around and access the environment of the city,\u201d Simon said. \u201cMy hope is to see my device in the streets \u2014 of New York at first, but in every city in the U.S.\u201d<\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

https:\/\/blogs.nvidia.com\/blog\/physical-ai-exoskeleton\/<\/p>\n","protected":false},"author":0,"featured_media":3984,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3983"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=3983"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3983\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/3984"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=3983"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=3983"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=3983"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}