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Robotics in Neurorehabilitation: Beyond the Hype—Understanding What It Can (and Cannot) Do

Dr. Rishabh Pathak
Over the past decade, robotic neurorehabilitation has become one of the most discussed innovations in neurological recovery. Robotic gait trainers, upper-limb rehabilitation systems, exoskeletons, and AI-assisted rehabilitation devices are increasingly being adopted by hospitals and rehabilitation centres worldwide. However, an important question remains: Are robots the future of neurorehabilitation—or are they simply another tool in the rehabilitation toolbox? As clinicians and researchers, we must move beyond marketing claims and focus on scientific evidence, patient selection, and clinical reasoning. What is Robotic Neurorehabilitation? Robotic neurorehabilitation involves the use of electromechanical devices that assist, guide, resist, or augment movement during therapy. These technologies include: • Robotic gait trainers • Wearable exoskeletons • Upper limb robotic rehabilitation devices • End-effector robotic systems • Sensor-based rehabilitation platforms • AI-assiste...
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Electroretinogram Artifact

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Dr. Rishabh Pathak

Electroretinogram (ERG) artifacts in EEG recordings are related to retinal activity and can produce specific patterns.

1.      Nature of Electroretinogram (ERG) Artifacts:

o ERG artifacts are produced by retinal activity in response to photic stimulation.

o These artifacts are distinct from photomyogenic artifacts and have specific waveform characteristics.

2.     Characteristics:

o ERG artifacts manifest as low-amplitude frontal artifacts from the retina that are time-locked to the strobe.

o  The waveform of ERG artifacts is monomorphic and less spike-like compared to other artifacts, with a field typically limited to specific frontal electrodes.

3.     Differentiation:

o  Covering an eye during stimulation can help diminish the artifact from the ipsilateral frontal polar electrode, aiding in identifying and distinguishing ERG artifacts from other types of artifacts.

o  Understanding the waveform and field distribution of ERG artifacts is essential for accurate interpretation and differentiation from pathological brain activity or other types of artifacts in EEG recordings.

Recognizing the unique characteristics of ERG artifacts and their association with retinal activity can assist in accurate EEG interpretation and the differentiation of these artifacts from other EEG patterns or abnormalities.

 

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