Publications by authors named "Rig Das"
Objective: Deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) is a common treatment for motor symptoms of Parkinson's disease but its influence on non-motor symptoms is less clear. Sleep spindles are known to be reduced in patients with Parkinson's disease, but the effect of STN DBS is unknown. The objective of our study was to address this knowledge gap.
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- The study investigates whether deep brain stimulation (DBS) for Parkinson's disease can improve sleep quality, particularly in the early stages of treatment.
- Polysomnography was conducted over three nights with 14 patients, and sleep patterns were analyzed to see if immediate improvements occurred with the start of DBS.
- Results showed significant sleep disruptions persisted despite stimulation, suggesting one night of treatment is not enough to affect sleep architecture in these patients.
Article Synopsis
- The study aims to improve sleep stage accuracy in Parkinson's disease by addressing challenges in sleep staging due to basal ganglia dysfunction.
- Involved 15 PD subjects monitored over 45 nights using advanced video polysomnography, with independent scoring followed by secondary review for discordant epochs.
- The new method achieved a high agreement rate of 96.58% in sleep stage classification, significantly improving upon traditional standards while highlighting specific challenges in identifying awake and non-REM stages.
Electromyography and Inertial Motion Sensors Based Wearable Data Acquisition System for Stroke Patients: A Pilot Study.
Annu Int Conf IEEE Eng Med Biol Soc
November 2021
Development of wearable data acquisition systems with applications to human-machine interaction (HMI) is of great interest to assist stroke patients or people with motor disabilities. This paper proposes a hybrid wireless data acquisition system, which combines surface electromyography (sEMG) and inertial measurement unit (IMU) sensors. It is designed to interface wrist extension with external devices, which allows the user to operate devices with hand orientations.
View Article and Find Full Text PDFStroke is one of the most common neural disorders, which causes physical disabilities and motor impairments among its survivors. Several technologies have been developed for providing stroke rehabilitation and to assist the survivors in performing their daily life activities. Currently, the use of flexible technology (FT) for stroke rehabilitation systems is on a rise that allows the development of more compact and lightweight wearable systems, which stroke survivors can easily use for long-term activities.
View Article and Find Full Text PDFStrokes are a growing cause of mortality and many stroke survivors suffer from motor impairment as well as other types of disabilities in their daily life activities. To treat these sequelae, motor imagery (MI) based brain-computer interface (BCI) systems have shown potential to serve as an effective neurorehabilitation tool for post-stroke rehabilitation therapy. In this review, different MI-BCI based strategies, including "Functional Electric Stimulation, Robotics Assistance and Hybrid Virtual Reality based Models," have been comprehensively reported for upper-limb neurorehabilitation.
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