In 2011, almost 100 million Americans were affected by at least 1 of the more than 1,000 neurological disorders, including stroke, migraine, epilepsy, traumatic brain injury (TBI), Parkinson’s disease (PD), Alzheimer’s disease (AD), and other dementias. Unfortunately, several of these neurological disorders exist without a cure, particularly these life-limiting diseases that affect the brain and the mind. Neurological health issues tend to be challenging to diagnose since the signs and symptoms of one neurological problem mimic another. Also, health issues that are not neurological conditions can sometimes be similar to the symptoms of neurological diseases. As neurological disorders increase due to an aging population, finding better ways to improve brain diagnosis is vital.
In the traditional hospital setting, diagnosing and screening for neurological disorders often entails neuroimaging, serum testing, lumbar puncture, electroencephalogram (EEG), nerve conduction studies, and electromyography. There is ongoing research to use technology to improve the diagnosis of medical conditions. For example, scientists are researching technologies most people use on their smartphones to aid in diagnosing brain disorders. Two include eye tracking and speech recognition to observe changes while the device monitors eye movements and analyzes speech patterns. Custom digital health app development can be crucial in checking feasibility and creating innovative solutions within this domain.
Eye Tracking for Brain Health
Eye tracking is a non-invasive tool used for screening and diagnosing neurological conditions. It measures and monitors eye movements, enabling early intervention and treatment. By analyzing eye movement patterns and gaze behavior, eye tracking records the person’s focus when viewing visual displays.
For instance, in sports science, eye tracking is used to enhance athletes’ thinking and cognitive abilities. Researchers use it to track their attention and focus when chasing after the ball or facing opponents. Similarly, eye tracking can notice patterns when a regular person starts changing how they see. One of the early symptoms of brain problems is affected eyesight, such as double vision, nystagmus, oscillopsia, and disorders of the pupils. This often happens because of proximity to the brain.
Eye tracking can potentially diagnose brain disorders more accurately than medical examinations. Analyzing changes in eye movements and gaze patterns can offer valuable insights into various neurological conditions. Consider these examples of how eye tracking proves beneficial:
- Eye muscle functions
- Rehabilitation
- Attention, memory, and focus assessment
Eye tracking can be an alternative to traditional eye exams by detecting early changes in eye movements. This method offers several advantages over expensive and time-consuming exams. Additionally, subjective tests have been known to identify healthy individuals or misdiagnose illnesses incorrectly.
Speech Recognition for Brain Health
Speech recognition technology, also known as Automatic Speech Recognition (ASR), has become increasingly prevalent in various applications and tools such as Siri, Alexa, and Google Home. This technology has seamlessly integrated into our daily lives, enabling us to interact with our smartphones, cars, and even video games using speech commands. In addition to virtual assistants and voice-operated devices, ASR holds immense potential within the healthcare domain.
Research indicates that algorithms and linguistic models have the capability to record and segment audio, convert it into a computer-readable format, and analyze it. This is achieved by detecting words in spoken language through a microphone and employing voice recognition technology to identify an individual’s voice. Computer algorithms are then utilized to process and comprehend the spoken words. With appropriate training, speech recognition software can be adapted to create a cost-effective, non-invasive diagnostic test for neurological disorders based on speech patterns. To bolster diagnosis, the following techniques can be used:
- Acoustic features from speech
- Linguistic features extracted from a speech transcription
- Results of a mini-mental state exam
A comprehensive understanding of the intricate and context-dependent aspects of human speech empowers speech recognition-based technology to improve the diagnosis and treatment of speech disorders like aphasia, dysarthria, and stuttering often associated with neurological ailments.
By harnessing computer programs capable of discerning between standard speech patterns and those impacted by these brain disorders, researchers can make substantial advancements in identifying these conditions. The incorporation of advanced computing techniques such as statistical models, neural networks, or machine learning further amplifies the efficacy of this technology.
Other Technologies for Brain Health
Individuals with brain disorders often turn to augmentative and alternative communication as a means of supplementing or replacing speech and writing. These methods commonly rely on gestures. By utilizing computer technology to detect and analyze such non-verbal forms of communication through gesture recognition, it becomes possible to enhance the accuracy of diagnosing neurological disorders.
Facial recognition technology has been developing for decades but is still an emerging field. The image capture process in clinical settings is standardized to ensure image quality. Facial-recognition-based detection is more accurate, objective, comprehensive, and informative than the routine diagnostic approach. It also makes it possible to improve healthcare system efficiency. The facial database volume could be expanded for future perspectives and investigated further for neurological disorders such as dementia and Alzheimer’s disease.
Neurofeedback systems focus on training patients to self-regulate specific neural chemicals through real-time feedback, working with the brain’s reward system. It consists of three main components: an imaging modality, a signal processing series, and a feedback presentation of this information to the patient. Neurofeedback training may be effective in improving brain function and tracking the progress of neurological disorders from the onset.
To Wrap Up
As science and technology continue to advance together, integrating cutting-edge technologies like eye tracking and speech recognition shows excellent potential for analyzing brain health. These innovative tools allow for precise monitoring and assessment, leading to early detection of cognitive impairments and personalized interventions. By revolutionizing brain health research and care, these technologies pave the way for targeted interventions that can significantly improve outcomes for individuals with neurological disorders.