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

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...

Environmental Artifacts

Environmental artifacts in EEG recordings can arise from various devices and sources in the patient's surroundings. 

1.     Description:

oSources: Environmental artifacts can result from the presence of numerous types of devices in the patient's environment during EEG recording.

oCauses: These artifacts may be due to electrical fields surrounding devices or the mechanical effects of devices on the patient or the patient's bed.

oCommon Source: The most common environmental artifact is often attributed to the alternating current (AC) present in the electrical power supply.

2.   Characteristics:

oFrequency: Environmental artifacts from electrical power supply noise typically exhibit a monomorphic frequency corresponding to the AC frequency (e.g., 60 Hz in North America).

oAmplitude: These artifacts are usually medium to low amplitude and may be present across all EEG channels or in isolated channels with poorly matched impedances.

3.   Differentiation:

oWaveform Analysis: Comparing the waveform characteristics, frequency, and distribution of environmental artifacts can help differentiate them from other types of artifacts, such as physiological artifacts or epileptiform discharges.

oTiming and Repetition: Environmental artifacts often have fixed durations, regular repetitions, and highly preserved waveforms, distinguishing them from seizure activity or other pathological patterns.

Understanding the nature and characteristics of environmental artifacts is crucial for identifying and mitigating their impact on EEG recordings. Proper recognition and differentiation of environmental artifacts contribute to the accurate interpretation of EEG data and help ensure the quality and reliability of EEG analysis in clinical and research settings.

 

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