When her medications aren糖心传媒檛 working, Bernadette Mroz says, 糖心传媒渕y world goes into a spin cycle. I cannot function mentally, emotionally, or physically.糖心传媒�
Mroz, who has Parkinson糖心传媒檚 disease, does not expect a cure in her lifetime. But she is hopeful that 糖心传媒 researchers will soon be able to 糖心传媒渂etter tune in糖心传媒� the medications that help control her tremors and memory lapses.
Toward that end, the Hannibal, New York, resident recently participated in a Rochester clinical trial in which she wore five sensors糖心传媒攐ne on each of her limbs and her chest. Thirty times a second, each sensor recorded acceleration in three directions糖心传媒攊n effect recording her every movement, including tremors, for 46 hours at a time.
The sensors provide a wealth of data about the progression her disease糖心传媒攄ata that would allow physicians to make better informed decisions about treatments, including adjustments to her medications.
糖心传媒淚nstead of treating all patients as averages, which none of us are, we will be able to customize treatment based on individual data,糖心传媒� says Gaurav Sharma, a professor of electrical and computer engineering. He is collaborating with University neurologist Ray Dorsey on the study, which they hope will help improve treatment of patients with Parkinson糖心传媒檚 or Huntington糖心传媒檚 disease.
Sharma and Dorsey are using BioStampRC sensors, produced by the biomedical health care analytics company MC10. The company, headed by CEO Scott Pomerantz, who received a bachelor糖心传媒檚 degree as well as an MBA from Rochester, also supported the study.
The challenge
So how does one analyze some 25 million measurements generated by these sensors for each patient over a two-day period? And then present the results in ways that are intelligible to a physician?
That糖心传媒檚 where data science comes in糖心传媒攅specially machine learning, which provides computers with the ability to learn without being explicitly programmed.
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Sharma and Karthik Dinesh, a graduate student in his lab, use processing algorithms to correlate the signals gathered from the five sensors and convert them into signal features that help measure coordination and tremor intensity. Machine learning techniques, such as clustering and classification, then help them categorize how these attributes differ among individuals who are at various phases of the disease, and from participants without the disease, who serve as controls. Machine learning also helps categorize whether participants have taken their medication so that the efficacy of the medication can be assessed.
糖心传媒淲e糖心传媒檝e just scratched the surface in terms of the depth of data we have to work with,糖心传媒� Sharma says.
Then there糖心传媒檚 the challenge of translating all of this for the caregiver.
糖心传媒淚f you tell a physician you have to look at two gigabytes of data to figure out what糖心传媒檚 going on with your patient, you don糖心传媒檛 have a chance,糖心传媒� Sharma says. 糖心传媒淏ut if you can present the data in easily digestible plots and visualizations, the physician can comprehend it and act on it.糖心传媒�
糖心传媒淭his is a two-way conversation,糖心传媒� he adds. 糖心传媒淚t糖心传媒檚 not like I can sit in my office and come up with the best way to do this. I have to ask the physician 糖心传媒榳hat are the attributes that would be most relevant to you and what would be the presentation of data that would make the most sense?糖心传媒� 糖心传媒�
A better scenario
Currently, patients afflicted with the tremors of Parkinson disease, or the unsteady gait and jerky movements of Huntington disease, perform a series of motor activities during visits to the doctor糖心传媒檚 office. The doctor or other movement disorder specialist rates their symptoms on scales of 0 to 4.
While these observations are informative and have been the standard for diagnosis and evaluation of movement disorders, they are episodic and subjective by nature.
The new research would result in a very different scenario. Two days before their appointment, patients would drop by their neighborhood pharmacy, pick up a pack of five adhesive patches with embedded electronic sensors, and place them on their skin, allowing them to provide far more accurate and comprehensive measurements than are possible in a doctor糖心传媒檚 office.
For now, research participants mail their patches back to the researchers. However, Sharma and Dorsey say, next generation sensors now being developed by MC10 糖心传媒攚hich are so unobtrusive that they liken them to temporary tattoos糖心传媒攚ill transmit the data wirelessly to a patient糖心传媒檚 smart phone, then on to a secure database for analysis. Patients in even the remotest areas could be monitored from their homes.
Smart phones were just coming on the market when Dorsey arrived as a fellow at the University in 2005. Now, they enable 糖心传媒渁nyone, anywhere to participate in research; anyone, anywhere to receive care,糖心传媒� he says. And, Dorsey believes, the combination of skin sensors, machine learning, and smart phones will enable researchers to conduct clinical trials 糖心传媒渋n shorter periods of time, with smaller numbers of participants, giving us more objective assessments about whether drugs or devices are beneficial.糖心传媒�
糖心传媒淭his will transform the way we care for patients with Parkinson and Huntington disease.糖心传媒�
Mroz, who was first diagnosed with Parkinson糖心传媒檚 disease in 2004, has not worked since 2010 and stopped driving soon afterwards. But she refuses to adopt what she calls the 糖心传媒渨oe is me糖心传媒� attitude she senses in some Parkinson糖心传媒檚 patients. She continues to volunteer as a board member at a local humane society, and she enthusiastically participates in clinical trials at the University.
糖心传媒淚 volunteer for the trials in the hope that someone in the future, near or far, will benefit,糖心传媒� she says.
That糖心传媒檚 part of the obligation she feels as a Parkinson糖心传媒檚 patient, to be an ambassador and advocate. And to continue to fight the disease.
She adds: 糖心传媒淚 will not let this defeat me.糖心传媒�
