{"id":170406,"date":"2025-07-03T13:10:44","date_gmt":"2025-07-03T19:10:44","guid":{"rendered":"https:\/\/tecscience.tec.mx\/en\/?p=170406"},"modified":"2025-07-07T13:24:50","modified_gmt":"2025-07-07T19:24:50","slug":"older-adults-regain-mobility","status":"publish","type":"post","link":"https:\/\/tecscience.tec.mx\/en\/health\/older-adults-regain-mobility\/","title":{"rendered":"Can Movement be Regained in Old Age? A New Non-Invasive Brain System Aims to Find Out"},"content":{"rendered":"\n

As we age, our movements begin to lose precision, speed, and strength. For older adults, this decline often results in reduced agility and coordination, which can lead to falls. This happens because, over time, the neurons responsible for motor skills<\/a> in the brain start to deteriorate. The effects can be compounded by neurodegenerative diseases like Parkinson\u2019s or Alzheimer<\/a>\u2019s, which further impair these abilities, even in younger individuals.<\/p>\n\n\n\n

With this in mind, researchers from Tec de Monterrey and the Instituto Polit\u00e9cnico Nacional (IPN), working together as part of the TEC-IPN Innovation Partnerships<\/a>, are collaborating on the development of a non-invasive brain rehabilitation system<\/strong> designed to help older adults regain mobility<\/strong> as they age.<\/p>\n\n\n\n

Luis Guillermo He<\/a>rn\u00e1ndez<\/a>, a researcher at the School of Engineering and Sciences<\/a> at Tec\u2019s Guadalajara campus<\/a>, explains that the neurorehabilitation platform combines non-invasive electrical stimulation, artificial intelligence (AI), and a robotic orthosis <\/strong>to simulate arm and hand movements. \u201cWe want to understand what happens to motor performance as people grow older and how we can help slow down that process,\u201d he says.<\/p>\n\n\n\n

A key element of the project is harnessing neuroplasticity<\/strong>\u2014the brain\u2019s ability to reorganize and adapt to recover lost functions. Using this technology, the researchers apply electrical stimulation to areas of the brain that have become less active over time to restore motor control.<\/p>\n\n\n\n

\r\n \r\n \"\"\r\n <\/picture>
Patients use a robotic orthosis with a joystick to assess their brain activity and movement performance. (Photo: Courtesy of Luis Guillermo Hern\u00e1ndez)<\/figcaption><\/figure>\n\n\n\n

Integrating Technologies To Identify Motor Difficulties<\/h2>\n\n\n\n

The system was designed by integrating three key technologies: electroencephalography<\/strong> (EEG), which measures brain activity; transcranial electrical stimulation<\/strong> (TES), which applies electrical currents to specific regions of the brain; and a robotic orthosis<\/strong> responsible for carrying out rehabilitation tasks. The setup also includes a computer interface<\/strong> with a screen that guides the patient through various exercises.<\/p>\n\n\n\n

\u201cWe place a helmet on the person\u2019s head, and through it we can both read and stimulate the brain<\/strong>. We also use a robotic device for the hand that allows the patient to perform exercises, like using a joystick or a mouse,\u201d Hern\u00e1ndez explains. The interface displays four points\u2014up, down, left, and right\u2014and the patient is asked to move a marker in a given direction.<\/p>\n\n\n\n

This technology allows researchers to assess how fast and accurately the patient\u2019s movements are<\/strong>. If tremors, slowness, or other issues are detected while performing the tasks, it becomes possible to identify signs of motor deterioration. If needed, brain stimulation can be activated as feedback.<\/p>\n\n\n\n

The patient wears a cap with electrodes placed on specific points of the scalp\u2014based on the 10-20 system\u2014to record or stimulate activity in related brain areas. If necessary, a transcranial current\u2014around 100 millivolts\u2014is applied to the premotor cortex, the region directly linked to initiating movement. To determine the appropriate current level, the team follows established clinical protocols that specify the frequency, duration, and stimulation cycles to ensure the procedure remains therapeutic and non-invasive<\/strong>.<\/p>\n\n\n\n

Hern\u00e1ndez describes AI as the \u201cheart\u201d of this brain-computer interface<\/strong>. It interprets EEG signals to determine whether the patient is attempting to move and whether they are experiencing any difficulty. It then makes real-time decisions about how to intervene\u2014for example, if the brain\u2019s motor areas are not activating properly, the system sends a signal to trigger stimulation. The AI also manages interaction with the robotic device, adjusting difficulty levels or interpreting movement performance.<\/p>\n\n\n\n

\r\n \r\n \"\"\r\n <\/picture>
The researchers used electroencephalography techniques to analyze how the brain behaves when people perform movements. (Photo: Courtesy of Luis Guillermo Hern\u00e1ndez)<\/figcaption><\/figure>\n\n\n\n

Validating The Technology With Older And Younger Adults<\/h2>\n\n\n\n

To better understand how the brain of an older adult behaves when performing basic motor tasks<\/strong>, the researchers conducted a series of clinical tests to measure, compare, and analyze brain activity before and after movement.<\/p>\n\n\n\n

The team worked with a sample of 30 individuals over the age of 50<\/strong>, along with a control group of younger adults between 20 and 49 years old. During the study, they observed differences in brain activity\u2014specifically in the beta band\u2014between the two groups. Older adults showed latency or delayed activation in the brain region responsible for movement<\/strong>. The beta band refers to a range of brainwave frequencies associated with voluntary movement, focus, and motor control.<\/p>\n\n\n\n

Hern\u00e1ndez explains that the team has completed the first phase of the project, which involved characterizing the population through EEG data. The next step, phase two, is to apply and evaluate the system to determine whether the stimulation can actually improve brain performance. The goal is to identify neural biomarkers<\/strong> that can serve as measurable indicators in validating the platform.<\/p>\n\n\n\n

\u201cWe need to give healthcare professionals a quantitative measure,\u201d he says. \u201cTo be able to say: look, this is helping the person because this brainwave or this part of their brain is now activating 50 or 30% better.\u201d He adds, \u201cwe\u2019re working to identify which biomarkers in those brain signals generate meaningful feedback with this new technology.\u201d<\/p>\n\n\n\n

The project is currently at Technology Readiness Level 6 (TRL 6), meaning the prototype has been developed and is functioning at a level of technological maturity that allows for clinical testing. While the system is currently focused on upper limbs like arms and hands, it could eventually be adapted to support rehabilitation of other parts of the body.<\/p>\n\n\n\n

\r\n \r\n \"\"\r\n <\/picture>
The platform uses AI to determine whether the patient is trying to move and experiencing any difficulty; it then makes real-time decisions to apply stimulation. (Photo: Courtesy of Luis Guillermo Hern\u00e1ndez)<\/figcaption><\/figure>\n\n\n\n

Collaboration Between Tec and IPN Scientists<\/h2>\n\n\n\n

Hern\u00e1ndez serves as the technical lead for the project at Tec de Monterrey and explains that the collaboration with researchers from IPN dates back several years, beginning with the joint development of the robotic orthosis. They secured funding for the project after winning the first TEC-IPN Innovation Partnerships grant, supported by both institutions and the Secretariat of Education, Science, Technology, and Innovation of Mexico City (SECTEI).<\/p>\n\n\n\n

Throughout the development process, the teams leveraged the strengths of both institutions. \u201cThe researchers at IPN have strong expertise in prosthetics electronics and are now also collecting muscular data. On our side, we specialize in biomedical signal analysis and in creating software that integrates all these technologies\u2014EEG, stimulation, and robotics\u2014and delivers it to the patient,\u201d says Hern\u00e1ndez.<\/p>\n\n\n\n

At Tec, contributors include researchers from the Neurotechnology and Brain-Computer Interface Lab, such as Javier Antelis<\/a>, Joel Huegel<\/a>, and Sof\u00eda Henao<\/a>. From IPN, the team includes scientists from the Medical Robotics and Biosignals Lab at the Interdisciplinary Biotechnology Professional Unit (Upibi), including David Cruz<\/a> and Mariana Ballesteros<\/a>.<\/p>\n\n\n\n

Hern\u00e1ndez notes that for clinical validation of the platform, they also plan to involve partner institutions like TecSalud<\/a> and the National Institute of Rehabilitation, with whom they\u2019ve already collaborated on previous projects<\/a>.<\/p>\n\n\n\n

\u201cWe\u2019d like to reach a point where this becomes a system people can use at home, because rehabilitation needs to be a daily, continuous process,\u201d he says. \u201cAnother goal is to give physicians a quantitative measure to evaluate how much progress a patient has made during rehabilitation.\u201d<\/p>\n\n\n\n

Did you find this story interesting? Would you like to publish it? Contact our content editor to learn more at marianaleonm@tec.mx<\/a> <\/strong><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers from Tec and IPN develop a neurorehabilitation system to help older adults with motor decline regain their abilities.<\/p>\n","protected":false},"author":47,"featured_media":170407,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_eb_attr":"","footnotes":""},"categories":[86],"tags":[135],"class_list":["post-170406","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-health","tag-school-of-engineering-and-sciences"],"acf":[],"yoast_head":"\nTec and IPN Develop AI to Help Seniors Regain Mobility | TecScience<\/title>\n<meta name=\"description\" content=\"Researchers from Tec de Monterrey and the Instituto Polit\u00e9cnico Nacional are developing a system aimed at helping older adults recover their motor abilities.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/tecscience.tec.mx\/en\/health\/older-adults-regain-mobility\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Can Movement be Regained in Old Age? 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