Unobtrusive Monitoring of Home-Based Post-Stroke Rehabilitation Exercises Using Heterogeneous Sensors

But is it better than these other sensors?

• motion-capture sensors (1)

• motion sensors (12)

• inertial sensors (4)

• force sensors (1)

• 3D inertial sensors (1)

• wearable sensors (10)

• nanosensors (1)

Unobtrusive Monitoring of Home-Based Post-Stroke Rehabilitation Exercises Using Heterogeneous Sensors

Idongesit Ekerete, Oonagh M. Giggins, Ian Cleland, Chris Nugent, and Jim McLaughlin
This paper proposes the use of heterogeneous sensors to unobtrusively monitor post-stroke rehabilitation exercises in a home environment. Rehabilitation exercises at home help post stroke sufferers to avoid long queues at health facilities and transportation problems associated with visiting these facilities. Experimental results demonstrated the ability to capture postures from a Heimann HTPA 32x32 thermal sensor, and speed and range during hand-stretching and gait-retraining exercises from a D2G Doppler radar sensor. Plans for future work are also outlined. I. INTRODUCTION Exercise rehabilitation is an integral part in the treatment of many conditions and particularly in the management of stroke. Rehabilitation in the home environment is an alternative aimed at decongesting health facilities and avoiding logistical complexities associated with transportation to these facilities [1]. Sensing technologies provide an opportunity to monitor post-stroke suffers as they undertake rehabilitation exercises at home. Many types of sensors have been previously used including wearable and video-based solutions, both having their advantages and disadvantages. Whilst they have been shown to provide high accuracy of the usability, wearable sensors are limited by their battery life and the forgetfulness of the user to charge and wear the device. Conversely, video cameras pose issues around privacy. These limitations can lead to inaccurate measurement of health parameters, the exercises not being undertaken effectively, non-compliance with the recommended protocol and subsequent discontinuation of a rehabilitation process [2]. This work proposes the use of nonwearable sensing solutions to monitor posture, range and speed of post-stroke patients during rehabilitation exercises in a home based setting. Information related to health parameters gathered during exercises such as posture, speed and range can help physiotherapists to ascertain if exercises have been performed as prescribed. 

AAAS Annual Meeting: Stretchable, Wearable Sensors for Stroke Rehabilitation

Until we get to this level of exact measurement of disabilities we will never be able to prove exactly how interventions work. 

AAAS Annual Meeting: Stretchable, Wearable Sensors for Stroke Rehabilitation

Photo credit: Elliott Abel/ Shirley Ryan AbilityLab

New technology could allow doctors to monitor the progress of stroke victims outside the hospital, serving as a game changer for patients and healthcare providers tackling the disease.
Researchers from Northwestern University—in partnership with Shirley Ryan AbilityLab—have created a new wearable sensor that sticks directly to the skin and moves with the body, providing detailed health metrics including heart function, muscle activity and quality of sleep. The research was presented at the American Association for the Advancement of Science (AAAS) Annual Meeting in Austin, TX Feb. 17.
“Stretchable electronics allow us to see what is going on inside patients' bodies at a level traditional wearables simply cannot achieve,” Northwestern University engineering professor John Rogers, who presented the research at the AAAS Annual Meeting said in a statement. “The key is to make them as integrated as possible with the human body.”
Rogers’s research team created a new bandage-like throat sensor that can measure a patient’s ability to swallow, as well as their patterns of speech. The sensor could aid in the diagnosis and treatment of aphasia, a communication disorder associated with strokes.
Speech pathologists generally monitor speech function using microphones that cannot distinguish between patients’ voices and ambient noise.
“Our sensors solve that problem by measuring vibrations of the vocal chords,” Rogers said. “But they only work when worn directly on the throat, which is a very sensitive area of the skin “We developed novel materials for this sensor that bend and stretch with the body, minimizing discomfort to patients.”
The throat sensors could be used in conjunction with electronic biosensors on the legs, arms and chest to monitor a stroke patient’s recovery progress. The intermodal system of sensors streams data wirelessly to clinician’s phones and computers, providing a quantitative, full-body picture of patients' advanced physical and physiological responses in real time.
“One of the biggest problems we face with stroke patients is that their gains tend to drop off when they leave the hospital,” Arun Jayaraman, a research scientist at the Shirley Ryan AbilityLab research hospital in Chicago and a wearable technology expert, said in a statement. “With the home monitoring enabled by these sensors, we can intervene at the right time, which could lead to better, faster recoveries for patients.”
The sensors are wireless, eliminating barriers posed by traditional health monitoring devices in clinical settings. Patients can wear them after leaving the hospital, allowing doctors to understand how the patients are functioning in the real world.
“Talking with friends and family at home is a completely different dimension from what we do in therapy,” Leora Cherney, research scientist at the Shirley Ryan AbilityLab and an expert in aphasia treatment, said in a statement. “Having a detailed understanding of patients' communication habits outside of the clinic helps us develop better strategies with our patients to improve their speaking skills and speed up their recovery process.”   

BeBop Sensors CEO shares his journey from building musical instruments to smart fabrics - stroke applications possible

With any stroke leadership at all we could be using sensors embedded in fabrics to objectively measure all incorect body movements and then create stroke protocols to correct those movements.
But never mind, we have NO stroke leadership and NO stroke strategy so not only are you screwed your children and grandchildren will be screwed.
The solution?
Destroy the existing stroke associations and replace them with survivor focused and run ones.

BeBop Sensors CEO shares his journey from building musical instruments to smart fabrics

A bi-articular model for scapular-humeral rhythm reconstruction through data from wearable sensors

With just the TINIEST BIT OF INITIATIVE any stroke clinician could run this same research using these sensors to come up with objective measurements on stroke muscular problems. And then create stroke protocols to fix those problems. This is so damned fucking easy, Why does it take a stroke addled survivor to even think of this ridiculously hard and difficult to implement research project? Do we have NO ONE in stroke that can rub two neurons together?  I should quit insulting our stroke medical professionals, it might hurt their fee fees. Oh well, I'm not running a popularity contest, I'm trying to solve stroke problems even if no one else is.
http://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-016-0149-2

• Federico LorussiEmail author,
• Nicola Carbonaro,
• Danilo De Rossi and
• Alessandro Tognetti

Journal of NeuroEngineering and Rehabilitation201613:40

DOI: 10.1186/s12984-016-0149-2

©  Lorussi et al. 2016

Received: 16 December 2015

Accepted: 14 April 2016

Published: 23 April 2016

Abstract

Background

Patient-specific performance assessment of arm movements in daily life activities is fundamental for neurological rehabilitation therapy. In most applications, the shoulder movement is simplified through a socket-ball joint, neglecting the movement of the scapular-thoracic complex. This may lead to significant errors. We propose an innovative bi-articular model of the human shoulder for estimating the position of the hand in relation to the sternum. The model takes into account both the scapular-toracic and gleno-humeral movements and their ratio governed by the scapular-humeral rhythm, fusing the information of inertial and textile-based strain sensors.

Method

To feed the reconstruction algorithm based on the bi-articular model, an ad-hoc sensing shirt was developed. The shirt was equipped with two inertial measurement units (IMUs) and an integrated textile strain sensor. We built the bi-articular model starting from the data obtained in two planar movements (arm abduction and flexion in the sagittal plane) and analysing the error between the reference data - measured through an optical reference system - and the socket-ball approximation of the shoulder. The 3D model was developed by extending the behaviour of the kinematic chain revealed in the planar trajectories through a parameter identification that takes into account the body structure of the subject.

Result

The bi-articular model was evaluated in five subjects in comparison with the optical reference system. The errors were computed in terms of distance between the reference position of the trochlea (end-effector) and the correspondent model estimation. The introduced method remarkably improved the estimation of the position of the trochlea (and consequently the estimation of the hand position during reaching activities) reducing position errors from 11.5 cm to 1.8 cm.

Conclusion

Thanks to the developed bi-articular model, we demonstrated a reliable estimation of the upper arm kinematics with a minimal sensing system suitable for daily life monitoring of recovery.

Sensoria and RespondWell Announce Wearable Rehabilitative Patient Monitoring at CES 2015

Seems like a no-brainer that our therapists could use this to determine our walking problems and then correct them.
http://globenewswire.com/news-release/2015/01/05/694845/10113949/en/Sensoria-and-RespondWell-Announce-Wearable-Rehabilitative-Patient-Monitoring-at-CES-2015.html

Smart tattoo sensors

Right now this seems limited but with any decent innovative thinking at all we could use this for stroke. But do you really think the ASA or NSA will take advantage of this to help stroke survivors?
1. Monitor INR levels because of warfarin use.
2. biofeedback on muscle movement.
3. Monitor brain functions after first stroke, send notices of problems to your smartphone and have it call 911.

“Smart Tattoo” Glucose Biosensors and Effect of Coencapsulated Anti-Inflammatory Agents

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Motorola patents e-tattoo that can read your thoughts by listening to unvocalized words in your throat
Would this be useful for aphasia?
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‘Smart tattoo’ may replace finger prick for diabetics

INR maybe? 

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Sensors with a smile: The smart 'tattoo' that can measure how tired you are

And your doctor could use this to monitor your fatigue and figure out exactly what causes it. Or is your doctor not willing to solve any of your stroke problems?

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Smart skin electronic tattoos the next leap in health tech

This membrane-like patch can be used to monitor body temperature, heartbeat, brain waves, aid muscle movement, and even help heal wounds

 

 

 

 

Multineurons is developing head-worn sensor & iPad app to monitor patients with brain disorders

We most certainly have brain disorders, so what is your doctor doing with this to determine your specific brain problems? Your doctor has to know specifically what damage has occurred. Or how will they come up with the correct stroke protocols to correct the problems and pass on the right prescriptions to the therapists? Because today they know absolutely nothing about your damage and are totally worthless in helping you recover. That statement should create dozens of flame wars in the comments.
http://medcitynews.com/2014/03/multineurons-developing-head-worn-sensor-monitor-patients-brain-disorders/?