Abstract: Handwriting is often taken for granted and seen as an easy task. However, mathematical data, when compared to qualitative and quantitative data, provides unique insights into the interaction between the Hand, Eye, and Mind (HEM). The cause of dementia is not known, and the world’s largest handwriting database should contribute to identifying possible causes and areas that need to be investigated. The northern hemisphere has a greater problem with dementia than the southern hemisphere. There are many questions that need to be asked. Does the rate of deterioration vary from country to country? Is the rate of deterioration dependent upon the blood type of the person? Is this mathematically reflected in the handwriting and mathematical data? Clearly, the more data retained in the database, the greater the accuracy of the HAST-Medicare program will become.
Key Words: Alzheimer’s, Dementia, Graphometry, Handwriting, HEM, HAST-Medicare, Qualitative and Quantitative Data.
Introduction: Handwriting is a brain impulse transmitted onto paper, reflecting the person’s mental and physical health. Upon reading several submitted papers on Alzheimer’s by various authors, it is apparent that none are handwriting experts and have made the repeated common mistake of using a 2-dimensional image of Alzheimer’s handwriting without understanding there are measurements that cannot be revealed in this type of image. This problem is compounded further by the fact that there are over 350 individual measurements that must be considered when measuring any kind of illness. If a Graphometrist researched one measurement a year, this would equate to 350 years before any graphic expression or written movement would be fully understood. Clearly, there needs to be a method where learning about graphic expression, how, and why is accelerated, and the use of Artificial Intelligence (AI) may provide the answer.
Alzheimer’s Handwriting: In the paper “Effect of Cognitive Fluctuation on Handwriting in Alzheimer’s Patient: A Case Study” by Emanuela Onofri, an example of Alzheimer’s handwriting and deterioration is shown. As seen in Figures 1A and 1B, the rate of deterioration within three days is evident. While the paper makes obvious observations like erratic spacing and some printed capitals, it highlights the need for comparative data to determine how common the rate of deterioration is within three days. In the paper “Dysgraphia in Dementia,” it is stated that “similarly, the dysgraphic deficits in dementias associated with movement disorders (e.g., CBD, HD, PSP, and PD) are poorly documented. Because some of the symptoms in these dementias can affect writing adversely (e.g., oculomotor difficulties, dyspraxia, hyper- or hypokinetic movements, etc.), most studies have focused on this aspect, and the spelling deficits (if any) have received little investigation.” This paper also highlights the need for a database that contains all forms of dementia so that similarities and dissimilarities can be compared.
Measuring Alzheimer’s Handwriting: The paper “Characterizing Earl-Stage Alzheimer through Spatiotemporal Dynamics of Handwriting” reveals the use of averages in “First, we assessed several state-of-the-art average spatiotemporal parameters, taken each separately: average velocity (𝑉𝑥), average jerk (𝐽𝑥), average acceleration (𝐴𝑥), average pressure (𝑃), total task time (T).” The use of averages is insufficient as it will set the ranges too wide when comparing large data points/sets. The data will not be sufficient to determine differences or specific similarities. The forensic paper “Changes in Handwriting due to Alzheimer’s Disease” is a serious paper that applies Forensic Document Examination techniques. This is totally different from the previous papers mentioned, which ignore the experience of a professional document examiner and highlight the problem that some academics ‘think’ expertise of this kind is not required.
Qualitative and Quantitative Data: The papers “Effect of Cognitive Fluctuation on Handwriting in Alzheimer’s Patient,” “Dysgraphia in Dementia,” and “Characterizing Early-Stage Alzheimer through Spatiotemporal Dynamics of Handwriting” do not take into account or compare non-handwriting data such as blood pressure, heart rate, height, or weight, etc., and then compare it to characteristics of handwriting. This means vital data is missing that can lead to clues as to the cause of Alzheimer’s. There is a clear need to combine dynamic handwriting data with other qualitative and quantitative data to ensure lifestyles are reflected in the handwriting. Handwriting data cannot be ignored as it is the only non-invasive method that can measure the rate of deterioration. Invasive medical tests that can measure the rate of deterioration are expensive, time-consuming, and burden the health system. Therefore, handwriting is a far cheaper option that should be considered as a viable alternative and solution.
HAST-Medicare: B2BXB has already developed HAST-Medicare, which collects qualitative and quantitative data and allows comparison against dynamic handwriting data (real-time). HAST-Medicare already stores blood pressure, heart rate, and other measurements calculated from handwriting (see HAST-Medicare on the B2BXB website Med-HAST – B2BXB). The advantage of HAST-Medicare data points is that they can be directly compared to other qualitative and quantitative data, whether it be through interviews, consultations, or medical tests. This means the HAST-Medicare data can be independently validated, and HAST-Medicare can be used to validate other methods of data collection. In practice, HAST-Medicare can be used for any physical and mental illness and comorbid conditions. It is not strictly limited to dementia (Alzheimer’s) or other types of neurological disorders.
The Challenge of Dementia (Alzheimer’s): The challenge of dementia is to be able to detect and monitor the rate of deterioration in dementia patients through handwriting. This data will establish whether other dementia patients around the world suffer the same rate of deterioration and have similar lifestyles or not. If required, HAST-Medicare retains specific memory tests built within the program that allows the memory to be tested. This is particularly useful once the rate of deterioration has been detected. Memory tests are marked separately within the database so that the researcher can see the date of a certain memory test. Whether the researcher wants the dementia patient to execute a clockface with a certain time or play a video or display a picture, it will reveal if the dementia patient’s memory has stayed the same, improved, or deteriorated.
Need for AI: There is a future role for Artificial Intelligence (AI) within the world’s largest handwriting database (including qualitative and quantitative data). AI does not need to calculate every variation of a letter ‘a’ but rather process qualitative and quantitative data for similarities or dissimilarities of each person’s lifestyle in each country and compare this to dynamic handwriting data. This approach will be able to predict the rate of deterioration and provide effective care packages for dementia patients, including families and loved ones.
Discussion: Graphometry is not Graphology or some crystal ball fortune telling. Graphometry is based upon mathematics and physics and provides objective data. Mathematics is either right or wrong; there are no grey areas or subjectivity. Dementia deserves the world’s largest anonymous database to identify commonalities and similarities. This worldwide problem deserves worldwide cooperation and collaboration with all international organizations, hospitals, consultants, charities, and researchers.