Category: Parkinson’s

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Brain Parkinson's

qMRI for early detection of Parkinson’s disease

Aviv Mezer and Hebrew University colleagues used quantitative MRI to identify cellular changes in Parkinson’s disease. Their method enabled them to look at microstructures in the striatum, which is known to deteriorate during disease progression. Using a novel algorithm developed by Elior Drori, biological changes in the striatum were revealed, and associated with early stage Parkinson’s, and movement dysfunction.

qMRI achieves its sensitivity by taking several MRI images using different excitation energies. The researchers used this to reveal changes in the tissue structure within distinct regions of the striatum. Previously, the structural sensitivity of these measurements could only be seen post mortem. 

Mezer’s goal is to facilitate early diagnosis of the disease, and provide markers for monitoring the efficacy of future therapies. He also seeks to identify subgroups within the population suffering from Parkinson’s disease – who may respond differently to some drugs than others, leading to personalized treatment. He will now use the technique to investigate microstructural changes in other regions of the brain. The team is in the early stages of developing a qMRI into a tool that can be used in a clinical setting.

Join ApplySci at MIT on September 30 for Deep Tech Health + Neurotech Boston

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AI Brain Parkinson's

Neural Network assesses sleep patterns for passive Parkinson’s diagnosis

MIT’s Dina Katabi has developed a non-contact, neural network-based system to detect Parkinson’s disease while a person is sleeping.

By assessing nocturnal breathing patterns, the series of algorithms detects, and tracks the progression of, the disease — every night, at home.

A device in the bedroom emits radio signals, analyzes their reflections off the surrounding environment, and extracts breathing patterns, without bodily contact. The breathing signal is then fed to the neural network to assess Parkinson’s Disease in a passive manner.

Current diagnosis methods are invasive, expensive, and must be done at specialized centers, making frequent testing almost impossible.

Katabi said that a relationship between Parkinson’s and breathing was noted in 1817, motivating her to explore this form of detection, and that respiratory symptoms manifest years before motor symptoms.

Join ApplySci at MIT on September 30th for Deep Tech Health + Neurotech Boston

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Brain Parkinson's

Joe Wang developed, closed-loop, levadopa delivery/monitoring system for Parkinson’s disease

Early Parkinson’s Disease patients benefit significantly from levodopa, to replace dopamine to restore normal motor function. As PD progresses, the brain loses more dopamine-producing cells, which causes motor complications and unpredictable responses to levodopa. Doses must be increased over time, and given at shorter intervals. Regimens are different for each person and may vary from day-to-day.

Currently, clinicians assess levodopa’s benefit by patient testimony and clinical exam, making it difficult to determine optimal treatment. Novel levodopa delivery strategies and wearable sensors that track symptoms and disease progression have been created, but levodopa levels in the body have not been monitored in real time.

Joe Wang and colleagues have developed a closed loop levodopa delivery system. A network of physical and chemical sensors monitor levodopa levels and inform a delivery device, guided by algorithms, creating a personalized regimen. This can finally optimize the therapeutic management of Parkinson’s Disease.

Join ApplySci at MIT on September 30th for Deep Tech Health + Neurotech Boston

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Brain DBS Parkinson's

Directional DBS system targets GPi to relieve Parkinson’s symptoms

Abbott received FDA approval for an expanded indication for its Deep Brain Stimulation system, to include targeting of internal globus pallidus. The GPi plays an integral role in motor function. When targeted with DBS, Parkonson’s symptoms not adequately controlled by medication can improve.

The directed stimulation system is now approved for all major targets used to treat movement disorders, using an iOS software platform and Bluetooth.

The company’s PROGRESS study is the largest DBS study for directional lead use in Parkinson’s disease.

Abbott’s Erika Ross will discuss advanced neurmodulation technologies at ApplySci’s Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 11-12, 2020

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Parkinson's Sensors

Wearable haptic feedback/stimulation band to address Parkinson’s symptoms

Microsoft has submitted a patent application for a wearable band that uses haptic feedback for stimulation when wrapped around limbs or joints.  It is meant to alleviate Parkinson’s symptoms, including tremors and muscle stiffness.

Haptic actuators are distributed across a band that is adjusted to a  “duty cycle” which responds to data derived from wearable sensors, including accelerometers, gyroscopes, heart-rate sensors, and electromyography sensors, as well as tablets or phones.

Examples include stylus sensors communicating with a wrist-worn device to detect involuntary motion while writing. The actuators would then be used to reduce the involuntary motion.  The wearable itself could also detect the motion of the actuators.

The patent describes stimulation “provided through the vibration of two or more actuators within the wearable device. In various examples, the wearable device may additionally comprise a second channel for the provision of therapeutic stimulation, such as an audio channel (e.g. the wearable device may additionally comprise a speaker or buzzer),”

The sensors could be integrated into a patch on a shoulder or other joint, or into clothing.

Join ApplySci at the 10th Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 21-22 at Stanford University — Featuring:  Zhenan Bao – Christof Koch – Vinod Khosla – Walter Greenleaf – Nathan Intrator – John Mattison – David Eagleman – Unity Stoakes – Shahin Farshchi – Emmanuel Mignot – Michael Snyder – Joe Wang – Josh Duyan – Aviad Hai – Anne Andrews – Tan Le – Anima Anandkumar – Hugo Mercier

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Brain Conference Parkinson's Ultrasound

Focused ultrasound thalamotomy in Parkinson’s Disease

UVA’s Scott Sperling and Jeff Elias, who already used focused ultrasound to treat essential tremor, have just published the results of  a small study showing the efficacy of the technology in Parkinson’s Disease.

The sound waves were shown to interrupt brain circuits responsible for the uncontrollable shaking associated with the disease. The researchers claim that their study also offers “comprehensive evidence of safety” in its effect on mood, behavior and cognitive ability, which has not previously been studied.

According to Sperling, “In this study, we extended these initial results and showed that focused ultrasound thalamotomy is not only safe from a cognitive and mood perspective, but that patients who underwent surgery realized significant and sustained benefits in terms of functional disability and overall quality of life.”

27 adults with severe Parkinson’s tremor that had not responded to previous treatment were divided  into two groups. Twenty received the procedure, and a control group of seven (who were later offered the procedure) did not. Participants reported improved quality of life, including their ability to perform simple daily tasks, emotional wellbeing, and a lessened sense of stigma due to their tremor, at both three and twelve months.

The team found that mood and cognition, and the ability to go about daily life, ultimately had more effect on participants’ assessment of their overall quality of life than did remor severity or the amount of tremor improvement.

Cognitive decline was seen in some participants after the study, in that they were less able to name colors and think of and speak words. The cause of this was unclear, and must be investigated. The researchers suggested this could be a result of the natural progression of Parkinson’s.

Join ApplySci at the 10th Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 21-22 at Stanford University — Featuring:  Zhenan Bao – Christof Koch – Vinod Khosla – Walter Greenleaf – Nathan Intrator – John Mattison – David Eagleman – Unity Stoakes – Shahin Farshchi – Emmanuel Mignot – Michael Snyder – Joe Wang – Josh Duyan – Aviad Hai – Anne Andrews – Tan Le

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Brain Parkinson's

Implanted sensors track dopamine for a year

Helen Schwerdt, Ann Graybiel, Michael Cima, Bob Langer, and MIT colleagues have developed and implantable sensor that can measure dopamine in the brain of rodents for more than one year.  They believe that this can inform the treatment and understanding of Parkinson’s and other brain diseases.

According to Graybiel, “Despite all that is known about dopamine as a crucial signaling molecule in the brain, implicated in neurologic and neuropsychiatric conditions as well as our abilty to learn, it has been impossible to monitor changes in the online release of dopamine over time periods long enough to relate these to clinical conditions.”

The sensors arenearly invisible to the immune system, avoiding scar tissue that would impede accuracy. After  implantation, populations of microglia  and astrocytes were the same as those in brain tissue that did not have the probes.

In a recent animal  study, three to five sensors per were implanted 5 millimeters deep in the striatum. Readings were taken every few weeks, after dopamine release was stimulated in the brainstem, traveling to the striatum. Measurements remained consistent for up to 393 days.

If developed for use in humans, these sensors could be useful for monitoring Parkinson’s patients who receive deep brain stimulation.

Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include:  Rudy Tanzi – Mary Lou Jepsen – George Church – Roz Picard – Nathan Intrator – Keith Johnson – John Mattison – Roozbeh Ghaffari – Poppy Crum – Phillip Alvelda –Marom Bikson – Ed Simcox – Sean Lane

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AI Music Pain Parkinson's Sleep

AI driven, music-triggered brain state therapy for pain, sleep, stress, gait

The Sync Project has developed a novel, music-based, non-pharmaceutical approach to treating pain, sleep, stress, and Parkinson’s gait issues.

Recent studies showed Parkinson’s patients improved their gait when listening to a song with the right beat pattern, and post surgery patients used 1/3 the amount of self-administered morphine after listening to an hour of music.

Lifestyle applications include Unwind, an app detects ones heartbeat, and responds with relaxing music (customized by machine learning tools) to aid sleep, and the Sync Music Bot, which uses Spotify to deliver daily music to enhance work, relaxation, and exercise.

With further clinical validation, this non-invasive therapy could replace drugs for better, targeted, personalized interventions.

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen – Daniela Rus

Registration rates increase Friday, July 14th

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Monitoring Parkinson's Sensors Wearables

Verily’s health sensing research watch

The  Verily Study Watch passively captures health data for continuous care platforms and clinical research. Key features described by the company include:

  • Multiple physiological and environmental sensors are designed to measure relevant signals for studies spanning cardiovascular, movement disorders, and other areas. Examples include electrocardiogram (ECG), heart rate, electrodermal activity, and inertial movements.
  • A long battery life of up to one week in order to drive better user compliance during longitudinal studies.
  • Large internal storage and data compression allow the device to store weeks’ worth of raw data, thus relaxing the need to frequently sync the device.
  • A powerful processor supports real time algorithms on the device.
  • The firmware is designed to be robust for future extensions, such as over-the-air updates, new algorithms, and user interface upgrades.
  • The display is always on so that time is always shown. The display is low power and high resolution for an appealing look and a robust user interface. Note: currently, only time and certain instructions are displayed. No other information is provided back to the user.

The watch will be used in Verily’s current and forthcoming studies, such as the  Personalized Parkinson’s Project, meant to track progression, and the Baseline study, meant to understand transitions between health and disease.

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston – Featuring: Joi Ito, Ed Boyden, Roz Picard, George Church, Tom Insel, John Rogers, Jamshid Ghajar, Phillip Alvelda and Nathan Intrator – September 19, 2017 at the MIT Media Lab

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Parkinson's Virtual Reality

VR training to reduce falls in Parkinson’s, dementia

Tel Aviv University’s Jeff Hausdorff has created a virtual reality treadmill system in an attempt to prevent falls in Parkinson’s  and  dementia patients.

Current interventions focus on improving muscle strength, balance and gait.  By integrating motor planning, attention, executive control and judgement training, using VR, therapies can also address the cognitive issues associated with falls.

In a recent study of 282 participants,  146 did treadmill + VR training, and 136 did treadmill training alone. VR patient foot movements were filmed and shown on a screen, in order for them to “see” their feet walking  in real-time. The game-like simulation included avoiding and stepping over puddles or hurdles, and navigating pathways. It also provided motivational feedback.

Fall rates were similar in both groups before the training. Six months after, those who participated in the VR intervention fell 50% less. Those who did not train with VR had consistent fall rates. The biggest improvement was seen in Parkinson’s patients.

Patients can receive the combined therapy at the Hausdorff-led Center for the Study of Movement Cognition and Mobility at Tel Aviv’s Ichilov Hospital.

Click to view the Tel Aviv Sourasky Medical Center video.

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston – Featuring Roz Picard, Tom Insel, John Rogers and Nathan Intrator – September 19, 2017 at the MIT Media Lab

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Brain Parkinson's

Carbon electrode technique tracks dopamine in the brain

Michael Cima and MIT colleagues have developed a more precise tool to measure dopamine in the brain, to be able to study its role in in learning, memory, and emotion.

The new carbon electrode based technique can cover more of the brain, and provide longer, more accurate neurotransmitter readings, than previously possible.

The goal is a better understanding of neurtransmitter related diseases, and potential therapies to boost dopamine levels, in conditions that dysregulate it, such as Parkison’s disease.

According to lead author Helen Schwerdt: “Right now deep brain stimulation is being used to treat Parkinson’s disease, and we assume that that stimulation is somehow resupplying the brain with dopamine, but no one’s really measured that.”

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston – Featuring Roz Picard, Tom Insel, John Rogers and Nathan Intrator – September 19, 2017 at the MIT Media Lab
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Parkinson's Virtual Reality

VR for early neurodegenerative disease detection, personalized rehabilitation

Tomsk Polytechnic and Siberian State University scientists David Khachaturyan  and  Ivan Tolmachov have developed a VR based neurodegenerative disorder diagnosis system.  The goal is the early detection and tretment of diseases, including MS and Parkinson’s.  The next step is the use of VR systems, like Glass and Kinect, for personalized rehabilitation.

50 subjects, both healthy and already diagnosed, used VR headsets,  a non-contact sensor controller and a mobile platform during a variety of activities.  Changes in posture and balance were detected, and compared to a human  skeleton model of 20 points on the body.  Deviations from the model indicated disease.  Differences in reactions of those with difference diseases was also noted —  Parkinson’s patients experienced hand tremors, and others experienced compromised coordination.

A clinical trial  will be completed in 2017.

ApplySci’s 6th   Wearable Tech + Digital Health + NeuroTech Silicon Valley  –  February 7-8 2017 @ Stanford   |   Featuring:   Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Mary Lou Jepsen – Vivek Wadhwa – Miguel Nicolelis – Roozbeh Ghaffari – Unity Stoakes