NeurEYE Aims to Replace Subjective Functional Scoring With Sensor-Based Assessment
A Spanish observational registry is preparing to test whether video and audio captured in a smart-space setting can measure how neurologic disease alters daily functioning. The project, Advanced Multisensorial System for Automatic Assessment of Neurological Disorders in Smart Spaces, is designed to analyze activity performance with signal processing and machine learning rather than relying only on bedside judgment or recall-based questionnaires.
The study enters a crowded but clinically important problem: functional status in neurologic disease is still commonly judged through tools that can miss the quality of performance. Two people may obtain the same score while moving through an activity in very different ways, and those differences often matter for independence, caregiver burden, and rehabilitation planning. Direct observation by a clinician can also change behavior, which weakens the realism of the assessment.
Functional Independence Is the Outcome, but Performance Quality Is the Target
The registry is built around activities of daily living, the practical tasks that determine whether a patient can live independently or needs assistance. In neurologic disease, loss of these abilities often signals disability long before a dramatic neurologic event forces the issue. The protocol argues that functional evaluation should happen in an ecological context, because real-world performance reveals limitations that office-based assessments can miss.
One sentence captures the clinical problem in plain terms: standard scoring can hide how a patient actually moves, compensates, or struggles.
The planned system, NeurEYE, is meant to extract indicators of neurologic impairment from sensory systems embedded in intelligent spaces. Those data will be processed with machine learning to identify functional limitation while the person performs a daily activity. The project also aims to describe limitations in a controlled environment that resembles routine patient context, a design that could reduce the distortion caused by a formal examination room.
A Case-Control Registry With Healthy Controls and Neurologic Disease Cohorts
The study is listed as an observational case-control registry with a cross-sectional time perspective and an estimated follow-up duration of three years. Enrollment is estimated at 50 participants. Adults 18 years and older are eligible, and both sexes may participate. Healthy volunteers are accepted.
Participants are divided into two device-based cohorts: healthy people and people with neurologic diseases. The control group will be recruited through non-probability convenience sampling from the researchers’ immediate circle. The experimental group will include adults diagnosed with a neurologic disease, recruited through non-probabilistic consecutive sampling from collaborating hospitals and patient associations, including the Spanish Federation of Parkinson’s Disease Associations, the Synaptia Vithas Neuroscience Institute, the University Hospital of Guadalajara, and the National Paraplegic Hospital of Toledo.
The inclusion criteria narrow the neurologic cohort to people with time since diagnosis, a Mini-Mental State Examination score between 10 and 30, a Barthel Index score between 100 and 61, and stable medical treatment for three months before assessment. Exclusion criteria remove people with musculoskeletal disorders, cardiovascular disease, respiratory disease, metabolic disease, or other conditions that could interfere with testing, as well as those unable to sign informed consent.
Why Clinicians Still Struggle to Measure Disability Cleanly
Conventional functional scales carry familiar weaknesses. There is no established gold standard for functionality, and many tools say little about how well an activity is performed. Administration can be time-consuming, and observational scoring is vulnerable to bias from sex, culture, interviewer behavior, and the participant’s awareness of being watched.
Self-reported measures bring a different problem: recall bias. People may minimize their symptoms, fail to recognize the severity of their limitation, or describe performance in a way that is not fully realistic. Even when clinicians are trained to administer observational tools carefully, subjectivity still creeps in. This is where sensor-based monitoring becomes attractive. The promise is not simply more data, but more objective data tied to the actual mechanics of function.
The protocol links the project to broader scientific and health priorities in Spain and Europe, including the Health priority of the State Plan for Scientific Research and the Health Cluster within Horizon Europe. The project is also described as part of a combined effort with the University of Seville and the University of Alcalá de Henares, with URJC leading the methodology and clinical validation component.
Disability Measurement Could Shift From Impression to Quantification
Neurologic disease is already a major driver of disability in Spain, responsible for 44% of disability due to chronic diseases and 50% of years lost due to disability, as described in the study record. In that context, even modest improvements in measurement could matter. A system that records how a person actually completes a task could refine the level of disability assigned to the patient, and it could also support individualized reports based on sex, activity, and functional pattern.
This matters because rehabilitation decisions depend on specifics. A patient who completes an activity slowly, with compensatory movements or altered sequencing, may need a different intervention than someone whose score looks similar on paper but whose performance is more efficient. By capturing qualitative and quantitative alterations, the platform is meant to help clinicians identify early disability, improve diagnosis, and adapt rehabilitation treatment to specific functional needs.
The device intervention itself is straightforward in the registry description: NeurEYE will be used in healthy people and in people with neurologic diseases. The data captured are described as video and audio recordings, with signal analysis used to generate the functional indicators. No trial results are posted yet, and the study is not yet recruiting.
A Small Registry With Large Ambitions for Rehabilitation Practice
The study is still at the planning stage, so the central question is operational rather than outcome-based: can a multisensory platform produce clinically meaningful disability metrics that improve on current observation-based methods? The record does not provide performance data, accuracy metrics, or comparative endpoints yet. It does make clear, however, that the design is aimed at reducing examiner bias and grounding disability assessment in observed behavior rather than recollection or impression.
The practical consequences would extend beyond scoring. If the system can reliably distinguish how neurologic impairment changes daily activity, clinicians could use those measurements to build more precise rehabilitation plans and monitor change over time. If it cannot, the field will still be left with the same old gap between what a clinician sees in the room and what a patient actually does at home or in daily life.
One concrete limitation is already visible: the protocol relies on a small estimated sample of 50 participants, and the control group is recruited by convenience sampling. The study also spans several collaborating centers and associations, which may help recruitment but will require careful consistency in how activities are captured and analyzed. The record leaves the technical validation question open, and that question will determine whether smart-space monitoring becomes a useful neurologic tool or remains a promising engineering concept.