1. Undergraduates: Daniel Croitoru and Hye Ryong Sin
Category: Engineering and Technology
Degree Level: Bachelors Degree
Abstract ID# 77
Signature Testing Analysis and Research
Daniel Croitoru, Hye Ryong (Heather) Sin, and Naiqian Zhi
Pls: B. Kris Jaeger  Co-Pls: Riphat Sipahi, Andrew Gouldstone
Department of Mechanical & Industrial Engineering
Abstract
This work supports a larger research initiative to help Parkinson's patients.
People with tremor and Parkinson's disease struggle to complete daily tasks such
as writing and eating. Our research team has taken the initiative to design products
to facilitate such tasks for people with Parkinson's disease. In addition, a variety of
treatments and therapies exist to help improve tremor conditions. Patients'
handwriting is analyzed so that the effectiveness of each devices or intervention
can be measured and/or the progression of the disease can be tracked. The
purpose for this work is to identify suitable media which subjects with tremor can
utilize to submit handwriting samples for analysis. Patients send in their signatures
through various means such as fax, scans, and photographs. However, each time
the original is re-imaged, the quality of the signature sample worsens.
Our research focuses on identifying suitable re-imaging methods that don't
significantly alter signature quality. Using a MATLAB program, metrics of a patient's
signature, such as area, ink deposit, and density were collected and compared with
those of healthy signatures. Once these signatures were collected, statistical
analyses were conducted to establish which media produce re-imaged signatures
comparable to the originals for further analysis. Following ANOVA, post-hoc T-
tests were used to determine which re-imaging methods yield suitable data for
patients to send in their signatures. Prior to designing a product, a need for a
solution must be established and goals must be set. Accurate data from subjects
allows the research team to track the effectiveness of devices and interventions
on Parkinson's symptoms.
Conclusions:
After gathering information on the metrics of each reimaged signature and conducting t-tests,
we have concluded that the high quality scan, photocopy, and double photocopy –in that
order– will produce samples with the strongest similarity to the original samples.
Valid data is essential for a successful design that will meet its intended needs. This project is
part of a larger initiative to design innovative handheld devices that will facilitate daily tasks for
people with Parkinson’s disease. When the design team is drafting design goals, they evaluate
signature samples from patients with Parkinson’s disease. With the results of our research, the
design team will know to trust samples that were generated from high quality scans and
photocopies while being more skeptical of samples generated from other reimaging methods
such as cellular photograph and faxes.
In addition, handwriting can be used as a means of measuring the effectiveness of a certain
treatment or medication. If a doctor or physician is studying a sample that has been significantly
altered, they will be unable to draw valid conclusions and make recommendations regarding
future treatments. Our results verify which reimaging techniques are most accurate and reliable
enough to base predictions from.
Recommendations/Extensions:
While much of the NU undergraduate research focus in this initiative is mainly concerned with designing
pens and spoons to facilitate daily tasks for people with Parkinson’s disease, the applications of this work can be
used as a basis to test the adequacy of many other devices such as cups, pitchers, and other affordances that
require precision. Because writing is a direct product of muscular movements, the severity of the tremor is
propagated into the quality of the handwriting sample .
Introduction/Background:
As many as one million Americans are live with Parkinson’s disease (PD) [1]. PD is a chronic
neurologic condition that causes a gradual loss of muscle control and hand tremors which makes it
difficult for patients to complete simple tasks [2]. Because handwriting involves precision, it is often
analyzed to assess how effective a certain treatment is in treating the disease. Our project looked to
determine which reimaging method would produce a sample most similar to the original.
Parkinson’s disease is a chronic neurologic condition that causes a gradual loss of muscle control.
Those with PD may experience tremors, stiffness of the limbs, slow body movements, and poor balance
[3, 4]. Many doctors and physicians use handwriting analysis as a benchmark to track the disease’s
progress [5-7].
Acknowledgements:
1. US National Science Foundation, CBET 1133992
2. Mechanical and Industrial Engineering Department,
Northeastern University
3. Human Subjects Protection IRB #11-08-03
Any opinions presented on this poster are those of the
authors, not those of the funding agency.
Daily Challenges of Parkinson’s Patients:
Writing
Eating
Personal Hygiene
Dressing Sitting-Standing
References:
1. Smaga S. Tremor. American Family Physician 2003; 68(8): 1545-1552.
2. Samii A, Nutt JG, & Ransom BR. Parkinson’s disease. Lancet 2004; 363:
1783-1793.
3. Jankovic J. Parkinson’s disease: Clinical features and diagnosis. Journal
of Neurological Neurosurgy and Psychiatry 2008; 79: 368-376.
4. Jankovic J. Pathophysiology and clinical assessment of parkinsonian
symptoms and signs. Neurological Disease and Therapy 2003; 59: 71-
108.
5. Benito-León J & Louis ED. Essential tremor: Emerging views of a
common disorder. Nature Clinical Practice Neurology 2006; 2(12):
666-678.
6. Van Drempt N, McCluskey A, & Lannin NA. A review of factors that
influence adult handwriting performance. Australian Occupational
Therapy Journal 2011; 58(5): 321-328.
7. Ünlü A, Brause R, & Krakow K. Handwriting Analysis for Diagnosis and
Prognosis of Parkinson’s Disease. International Symposium on
Biological and Medical Data Analysis, LNCS 2006; 4345:441-450.
1. Preprocessing- signature sample is cleared of noise
and cropped at its boundary
2. Calculation of Metrics
- Area: measures the whole
rectangle area for the entire
signature in pixels
- Ink: measures how many ink
pixels have been utilized in
the entire signature
- Density: measures the
relative densities of the
chunks in percentage values
and po, the slope of the
linear interpolation of the
densities.
SQ
HQ
PHOTOCOPY
DOUBLE
PHOTOCOPY
CHEM DEPT FAX
220 SN FAX
CAMSCANNER
Personal Hygiene