Project Description

Monitoring and Tracking in Life

Balance 1.0

Team:

Karley Herschelman, Computer Science, kherschelman2012@my.fit.edu

Dylan Anthony, Computer Science, danthony2012@my.fit.edu

Jessica Cushman, Bio-medical Engineering, jcushman2011@my.fit.edu

Kristopher Bloom, Bio-medical Engineering, kbloom2012@my.fit.edu

Paige Carlton, Bio-medical Engineering, pcarlton2012@my.fit.edu

Juston Dias, Computer Engineering, juston706@gmail.com

Faculty Sponsors:

Dr. Ribeiro, Computer Science, eribeiro@cs.fit.edu

Dr. Mitra, Bio-medical Engineering, kmitra@fit.edu

Summary

    We plan to put pressure (and possibly heat) sensors in shoe inserts to measure the pattern of a person’s walk. The results will be interpreted and sent to an Android/IOS app. A person’s balance can tell many things such as their posture and memory ailments. By reporting these results with suggestions and notifications for improvement people will be able to catch these symptoms early to either monitor themselves or go to a doctor for further investigation. The team does see a potential for diagnosis capabilities in the future using our device. However, given the nature of a year-long project we will focus for the next year on the development of a personal-monitoring system with constant feedback for the user on the basis of improved quality of life.

Introductory Material

    Many common age-related complications affect quality of life. These complications could be detected in their early, and most treatable, stages with the analysis of balance utilizing a step-pressure monitoring device. The use of footwear: shoes, socks and/or inserts, for balance and foot pressure monitoring and/or record progression of Parkinson’s, dementia, memory loss, and fatigue; in addition to various other neurological/physical complications, including: arthritis (hips/knees), posture, and balance. Additionally, the technology can be applied to patient monitoring. With the aging population, a large concern is falling without being able to stand back up. Currently, there are various services that provide emergency contact notification systems, however the user must wear a clunky, often uncomfortable, and nondiscrete device which they have to manually trigger. Developing a discrete shoe insert can dramatically improve the quality of life for the elderly and provide peace of mind for their younger relatives with a built-in notification system that will contact the relatives if the system finds that the user is suddenly no longer on their feet; a closed-feedback system utilizing a weight sensor.

Analysis and Definition of the Problem

Important for use in elderly/aging patients to made aware of their movements before problems occur, such as sacroiliac joint dysfunction. Monitoring gait and pressure (length of step and with what force) while a patient is walking can also diagnose uneven legs (if one leg is longer/shorter, which can cause arthritis in hips in the mid-stage of life) or a limp. This early detection can pave the way for early detection.

Parkinson’s disease is a neurodegenerative movement disorder and is commonly characterized by resting tremors, bradykinesia (impaired ability to adjust the body’s position), rigidity, and an unstable posture [1]. Additionally, Tillman, et al [1] noted that with progressive resistance training, patients with Parkinson’s disease can improve their motor control. However, they also note that little is known about the effects of this treatment modality on gait and balance measurements in people with Parkinson’s. Tracking balance from the beginning to end of resistance training will provide caregivers and physical therapists a  better look at improvements or continued degradation. The study also reviews other findings and noted they were inconclusive due to the wide range of devices used for measurement. Therefore, the study concluded there is a clinical need for a device such as this. Gait disturbances causing falls are the highest concern in people with Parkinson’s disease [2]. Balash, et al. [2] reports that 38% to 68% of outpatients with Parkinson’s disease fall and is a primary cause of decreasing quality of life.

People are in early development of dementia but have not yet shown typical behavior of dementia can be diagnosed/predicted by changes in walking long before any observable cognitive changes occur.

References

  1. Tillman, Alex, et al. "Lower limb progressive resistance training improves leg strength but not gait speed or balance in Parkinson’s disease: a systematic review and meta-analysis." Frontiers in aging neuroscience 7 (2015).

  2. Balash, Yacov, et al. "Falls in outpatients with Parkinson's disease." Journal of neurology 252.11 (2005): 1310-1315.