Deans' stroke musings: A LabView Based Real-time Gait Monitoring and Wearable Suit for Stroke Rehabilitation

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Sunday, January 4, 2026

A LabView Based Real-time Gait Monitoring and Wearable Suit for Stroke Rehabilitation

Finally, your competent? doctor can get an objective diagnosis of gait problems AND DELIVER EXACT REHAB PROTOCOLS! Oh, too bad your doctor has no protocols at all for your recovery! JUST USELESS GUIDELINES! And doesn't even know how fucking useless they are! Guidelines don't guarantee recovery, why doesn't your incompetent? doctor know that?

A LabView Based Real-time Gait Monitoring and Wearable Suit for Stroke Rehabilitation

Stephen Johna and Kolapo S. Allib,Ψ Faculty of Engineering, The University of the West Indies, Mona Campus, Kingston 7, Jamaica, West Indies a Email: preachdword3@yahoo.com b Email: kolapo.alli@uwimona.edu.jm Ψ Corresponding Author (Received 27 December 2024; Revised 28 August 2025; Accepted 05 September 2025)

Abstract:

This paper presents the findings of a study on real-time gait monitoring and wearable suit for post stroke rehabilitation of disabled persons. The study measured irregularities in their hips, lower back, feet, knees and ankles, non-invasively, as well as the walking speed. A prototype was developed with eight gait sensor circuits which are attached to a full body suit via suitable Velcro straps and placed at various regions of the body including the hip, lower back, feet, knees and ankles. Each circuit consists of an ESP8266 module programmed with an Arduino code. This allows the MPU6050 sensor within the circuit to measure both acceleration and angular velocity in three planes: x, y and z for each targeted region of the body and display them on waveform charts via a LabView graphical user interface. This is achieved by sending the data wirelessly from the sensor circuit to a suitable LabView VI on a computer via Transmission Control Protocol (TCP). Statistical evaluations of motion analysis on clinical trials were performed to know the effectiveness of the proposed system. The comparisons from the walking gait patterns results show that the standard deviations obtained for the angular accelerations in x, y and z planes ranged from 2.896 to 9.497 rad/s2, 1.856 to 6.6312 rad/s2 and 2.951 to 10.209 rad/s2, respectively, with the mean values ranged from 2.089 to 9.453 rad/s2, 1.519 to 7.556 rad/s2 and 1.276 to 5.938 rad/s2, respectively. The standard deviations were closed for the angular velocities in x, y and z planes ranged from 0.7231 to 1.9443 rad/s, 0.5509 to 1.527 rad/s and 0.3676 to 1.1791 rad/s with the mean values ranged from 0.2763 to 0.833 rad/s, 1.1849 to 2.6565 rad/s and 0.777 to 2.235 rad/s, respectively. The LabVIEW platform can offer diverse visualisation features for gait analysis. This study demonstrates the use of the platform to aid monitor patients with walking disabilities.

Keywords: Gait sensors, stroke rehabilitation, LabView TCP server vi, Clinical trials, gait speed and acceleration