What technologies are in development to help people who are paralyzed?

When people are paralyzed, they lose the use of their limbs. This can happen from accidents, illness, or injury. Not only it is hard for them to move around and live their lives as a healthy person would do, but depending on what caused the paralysis, there may also be limited control over how they speak or swallow food. Despite these difficulties, there are many technologies in development that can help people regain full mobility and communication abilities.

These include robotics for assistance with upper body locomotion and swallowing mechanisms that improve speech clarity. There are also new ways to monitor patients’ vital signs and provide sensory feedback that helps people feel more connected to their surroundings without any loss of autonomy.

The challenges of full robotic rehabilitation for paralyzed patients

Many severely disabled people can receive robotic forms of physical assistance that help them regain some locomotion and control their muscles. The most common applications are in upper-body robots, which help people move their arms and hands, and can restore function to a range of activities (such as reaching, grasping, writing, and typing).

There are also lower-body devices like walkers and wheelchairs that allow patients to use their legs again. Rehabilitation methods that use these technologies tend to rely on a combination of imaging data, force-sensing sensors in the patient’s muscles or joints, and small motors that activate the limbs.

In contrast to these high-fidelity devices, many robotic rehabilitation systems are low-fidelity and assistive. These systems provide a range of physical and psychological cues that allow patients to improve their abilities with this robotics.

For example, the system may suggest ways for patients to improve their muscle tone or encourage them to communicate what they need. These processes rely on information from sensors placed in the patient’s limbs, which provide close-up feedback on how much force the patient is using and how well they are performing the task.

However, robotic interventions that use low-fidelity approaches are less helpful for completely paralyzed patients because they cannot provide the necessary range of motion and feedback. There is also a limited ability to recover their motor skills because of the damage to their spinal cords. Researchers have to rely on devices that use patient self-exertion or on high-fidelity robotics that provide an assistive force and sensory cues, which can overlap with conventional physical therapy techniques (e.g., electrical stimulation). In general, these systems are designed to help users move their limbs through a full range of motion and support them in activities like feeding themselves or writing.

Augmentative and alternative communication (AAC)

For patients who have lost their ability to communicate clearly, or have become unable to do so at all, augmentative and alternative communication (AAC) devices can help them find ways to express themselves.

There are many forms of AAC devices, ranging from simple text-to-speech technologies (e.g., computer programs that read books aloud) to more sophisticated voice synthesizers capable of mimicking human speech sounds in real-time. Although these high-fidelity forms cannot accurately convey all the subtle aspects of language (e.g., intonation and repetition), they can improve communication and help test patients’ ability to understand what they are saying.

Swallowing systems

When people lose their ability to consume food by mouth, they are usually diagnosed with dysphagia, a condition that often requires feeding through a tube into the stomach. Unfortunately, many patients with dysphagia can still feel the desire to eat and drink, which makes it hard for them to adjust to their condition psychologically.

Many new devices can be surgically implanted into the body and provide some sensory feedback. One example of this is an artificial larynx that can produce sounds similar to a natural voice to comfort patients when they cannot speak (e.g., after surgery).

Another system monitors a patient’s speech and breathing to detect when they are about to consume food. Sensors placed under the patient’s tongue then stimulate their pharynx muscles to push the food away from their throat. This is an example of a therapy that combines robotics with high-fidelity sensor data and can promote autonomous consumption in paralyzed patients.

Monitoring vital signs and communication feedback

Many paralyzed patients also require chronic medical monitoring to determine how well they are recovering from their injuries. In some cases, this can include monitoring of vital signs (e.g., heart rate and oxygen saturation) or sense organs, such as the muscles or nerves in their bodies.

These tasks’ importance lies in ensuring that the patient’s body is performing normally and that they do not have any infections or discomfort. There are also ways to collect data about patients’ physical condition from wearable devices, such as accelerometers and heart rate monitors that record information about their movements and breathing.

The Internet of Things, wireless technologies, and machine-to-machine communications are further enabling the collection of this data, which allows clinicians to detect changes in a patient’s condition, who is operating the system (e.g., a caregiver), and what they need to do to maintain their health. These are all important functions that can help patients recover from their injuries in the long term, but they need to be monitored consistently and reliably.

Other therapies that use machine learning may also help robotic rehabilitation systems improve over time. For example, machine learning may be used to interpret the results of balance-challenged patients’ movements to suggest ways to improve. Similarly, deep learning advances enable intelligent data analysis that can interpret patient, communicative behavior for use in AAC devices.

Market trends and medical applications

As a result of these interdisciplinary developments, there is a growing need for new types of robotics that have the ability to assist with multiple aspects of rehabilitation. These systems will likely be able to monitor an injured person and provide personalized therapy with the help of embedded sensors and wireless technologies. They will also be able to interact with patients (e.g., through AAC devices) and be controlled by them or their family members.

There are already a number of rehabilitation robots available in the market, such as the Recon Jet and Ekso GT (both by Ekso Bionics). These systems use sensors to track patient movement and allow them to practice walking with minimal support. Although they do not provide a high level of assistance, they can help patients maintain their physical condition and reduce their risk of injury. The value of these products is likely to increase in the coming years, but we are still at the early stages of this development.

A different, more comprehensive approach to robotic rehabilitation is being developed by the Center for Personalized Technology, which is managed by the Department of Veterans Affairs and funded by the Defense Advanced Research Projects Agency. The organization has developed a suite of technologies that work together to create a fully integrated personal assistance system (PAS).

The PAS is able to monitor patients’ movement and progress, detect interpersonal tensions between caregivers and patients, recognize symptoms related to dementia or other conditions, recognize when a patient has fallen, and even provide patient support through AAC devices. This system uses multi-modal sensors that collect data from multiple body parts simultaneously (e.g., brain waves and body movement).

It is difficult to predict how far this kind of technology will be developed and whether it will help reduce the number of cases where a patient suffers from complications related to their injuries (e.g., falls and bed sores). For example, the PAS system uses AI to recognize fall risk and alert caregivers, but its value may be limited if patients turn out to be more at risk than they seem. This is because patients may forget or delay telling doctors about their symptoms. However, advances in machine learning are also likely to provide this type of personalized care later on in the future.

Future developments can also have an impact on medical devices that already assist patients with their rehabilitation. For example, the WiTrack system is an orthotic that focuses on improving walking performance via a combination of wearable sensors and a tablet interface. It is able to analyze the patient’s gait and movement patterns in real-time and then provide specific feedback to improve walking.

This system can be used by patients with multiple sclerosis or Parkinson’s disease, for example, who may otherwise suffer from challenges controlling their mobility. Although these systems are too new to have taken off in the market yet, it is clear that this type of personal assistance will be an important part of future rehabilitation systems.

In addition to their ability to improve quality and safety, these systems can also help reduce the costs of healthcare. For example, they could help detect falls in their early stages and provide the patient with support within moments. This should result in a fall prevention system that is more cost-effective than a fall detection system alone.

However, it is clear that there is still a long way to go until people with mobility impairments are able to consistently and reliably receive high-quality rehabilitation services. There will have to be hardware, software, and artificial intelligence improvements before these services are put into practice on an industrial scale.

Conclusion

Although robotic rehabilitation may seem very advanced in theory, it is still at the experimental stage of development. This is likely to remain the case for a few more years. However, there is a clear need for assistive robots to maintain mobility and independence in older individuals. This is because these systems can help them avoid slips, falls, and injuries that can reduce their quality of life and result in greater healthcare costs. As a result, these robots are likely to become an important part of future healthcare systems.

Despite their potential, many challenges need to be overcome before robotic rehabilitation systems can help patients on a larger scale. One of the major problems is that the technology is not yet advanced enough to provide high-quality services. Developers must also develop machine learning and artificial intelligence in such a way that they can adapt its use to individual patients and situations.

Another challenge comes from the fact that robotics is still not seen as being as cost-effective or accessible as other solutions. Therefore, healthcare providers may see products or services based on artificial intelligence as unnecessary expenses. However, this should change over time, and the systems that provide a higher level of assistance are likely to become more widely used over time. There are also significant discoveries being made in this area. As such, it is important to keep an eye on developments and how they develop over the coming years.