A Package Of Smartphone & Sensor-Based Objective Measurement Tools For Physical and Social Exertional...for Illness-limiting Capacities, 2023, Mahmood

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https://epublications.marquette.edu/cgi/viewcontent.cgi?article=3584&context=dissertations_mu

PhD thesis

A PACKAGE OF SMARTPHONE AND SENSOR-BASED OBJECTIVE MEASUREMENT TOOLS FOR PHYSICAL AND SOCIAL EXERTIONAL ACTIVITIES FOR PATIENTS WITH ILLNESS-LIMITING CAPACITIES

Arafat Mahmood
Department of Computer Science

Marquette University, 2023

Patients with several incompletely diagnosed and understood chronic diseases suffer from symptoms that limit their functional capacity. In particular, patients with chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) and long covid syndromes have variable fatigue, malaise, poor and unrefreshing sleep, and delayed post-exertional exacerbations of these symptoms. There are no specific tests for these patients to diagnose their diseases properly. These patients must be aware of their daily activities and energy expenditure. Even a little physical effort or socially extroverted behavior can make them tired and incapable of continuing their daily routine. A comprehensive summary of the measured activities at any particular time of the day will eventually help the patients take precautions and prevent any unwanted physical or social burnout.

To address the current problems faced by these patients, we used a pair of smart insoles and a wrist-worn sensor-integrated device to detect and measure eleven daily living activities accurately. We developed a smartphone application and utilized the smartphone’s microphone to analyze the recorded sound buffer and detect voice activities and high-level noise exposures. We also explored the smartphone’s sensors to compare with the smart insoles’ results.

This work presents a practical package for patients with limited functional capacities due to illness. We describe the design and development of a smartphone application that collects the data from the sensor device and microphone, sends them to a server for machine learning calculation, and provides a comprehensive summary by objectively measuring the activities. The application works as the core component of the package that connects all the other components via BlueTooth and uses the network protocol to send raw data to the server.

 

Never heard of smart insoles before but a quick search was enough to establish they're a thing in sports, particularly running and golf it appears. Looks useful. A word search in the thesis comes up with this

 

I am not sure that smart insoles would work for people who are housebound, migrating between bed, loo and sofa in bare feet, socks or slippers depending on the climate, and distributing mobility burdens between the limbs which hurt least at the time.

 

Yes, probably more suited to less severe pwME but then they're the ones typically participating in research. Insoles may(?) give more accurate step counts and additional info about gait disturbances which we discussed elsewhere as potentially being a useful marker of our ups and downs.

I did wonder how insoles would go in socks or slippers for those of us with the migratory pattern you describe. If they work in socks they might be a convenient way of measuring feet on the ground time - what the Bateman Horne people are working on. Also wonder if the gait disturbance detection extends to registering inability to walk in a straight line and to the sudden bumps resulting from collision with a door frame. Something like a 'wearer appears to be drunk' function might do the trick