Emerging pervasive sensing technology provides new ways to create persuasive systems that can help people improve their health. Much persuasive computing research has involved the exploration of researchers' hypotheses about the ways that such ubicomp sensing can improve health. This thesis aims to enable individual users to test their personal hypotheses about how their actions, as tracked by ubicomp sensors, and the interface tools that they elect to use, actually impact their health goals. The key contributions are to develop the infrastructure and interfaces for a new persuasive system to support personal health hypothesis evaluation.
A hypothesis is \an idea or explanation for something that is based on known
facts but has not yet been proved"1. It is also de ned as \a proposition, or set
of propositions, set forth as an explanation for the occurrence of some speci ed
group of phenomena, either asserted merely as a provisional conjecture to guide
investigation (working hypothesis) or accepted as highly probable in the light
of established facts"2. We de ne a personal health hypothesis as an individual's
belief about the ways that their actions a ect their health. For example, a person
may believe that if they signi cantly increase their level of physical activity, this
will improve their health, in line with current health recommendations [
A large body of persuasive and ubicomp research has explored research
hypotheses related to improving or maintaining health. For example, the seminal
work of Consolvo et al. [
The aim is to provide a framework and the required interfaces, which make it possible for an individual to de ne, formulate and evaluate personal health hypotheses. We will study researchers' hypotheses and identify a class of personal health hypotheses which individuals would like to evaluate. Then we will select the required data and ubicomp sensors to collect such data. A framework for this purpose wi ll be designed and implemented. This framework, will provide the possibility for individuals to manipulate data (add, edit, or delete), monitor, visualize, analyze and evaluate the results. Then we will evaluate the system in terms of usability of the interfaces, e ciency, performance and actual use.
This thesis involves an iterative process with the following stages: 1. Design an architecture for personal health hypothesis evaluation. 2. Implement the architecture, based on personis. 3. Create interfaces for hypothesis associated with physical activity and health (based on creating a hypothesis framework associated with sensors) 4. Conduct usability studies to assess whether people can use the interfaces e ectively and to gain insights into the ways people would like to explore personal hypotheses. 5. Field trial to learn about use.
The key contribution is de ning a new approach of personal informatics based on ubicomp sensing to achieve long term goals such as being healthier. We believe that our approach may be valuable if evaluation of a personal hypothesis encourages individuals to be creative and out their own approaches to achieving their goals. For a personal hypothesis, we are concerned with one participant, the individual person who wants to test a hypothesis. Therefore, despite the broader de nition of a hypothesis, we will not deal with population level outcomes. 3
The aim is to create an opportunity for a person to take a new form of control over the ways that they make use of ubicomp sensor technology to help achieve their health goals. The primary results are de ning elements of a personal health hypothesis and a proposed architecture, which are explained in this section.
As a foundation for de ning our approach, we introduce an illustrative scenario.
Alice has just been diagnosed with mild hypertension (high blood pressure). She decides she wants to try altering aspects of her lifestyle to tackle this. She has been given an overwhelming amount of literature and advice. This points to several possible hypotheses about reducing hypertension. She decides she would like to test the hypothesis: if I exercise more that will reduce my blood pressure.
Alice might buy an activity sensor device3 to track her activity levels, and a device to measure her blood pressure4. These ubicomp sensors could collect the data required to evaluate her hypothesis in the scenario.
We now can de ne the elements of a personal wellness hypothesis that can be assessed by a ubicomp sensing system. 1. The user must formulate a suitable hypothesis. It takes the form if I do X then I will see e ect Y over time period Z. 2. X and Y can be measurable by ubicomp sensors (potentially multiple sensors for each). 3. The user must establish the baseline values for X and Y. 4. The user must set appropriate goal values for X and Y. 5. The user must make use of the devices to measure X and Y over time period Z, making use of interfaces that are based on best practice for persuasive technologies.
We now illustrate this in terms of our scenario. Suppose Alice sets the
hypothesis: If I increase my level of activity, my blood pressure will drop. Armed
with her FitBit, she can easily collect long term data that measures at least
some aspects of her activity. Her starting point for assessing her hypothesis is
to establish her baselines for X (activity level) and Y (blood pressure). To get
the baseline, she should use the FitBit for a period of time, such as a week. For
example, this may indicate she typically walks 5,000 steps a day on work days
and 15,000 a day on weekends. Similarly, she can use the Withings device to
measure her blood pressure. This also needs to be done over a period of time.
This is because a single Blood Pressure reading is not a reliable indication of her
true blood pressure. So she may take the early morning and evening measures
each day for a week [
Monitor and maintain that increase during the 6 month period. She also needs to get a measure of her blood pressure at that time, following a similar process to that used to determine the baseline.
Although we illustrated our de nition in terms of our scenario, personal hypothesis evaluation can be applied much more broadly. For example, it could make use of other sensors, even for this hypothesis. There are also many other ubicomp sensors5 that could support other hypothesis involving, for example, weight, intensity of activity and glucose response. There is also considerable scope for people explore hypotheses about other aspects of their lives, such as altering behaviors to reduce carbon footprint. 3.2
The proposed architecture for hypothesis evaluation is shown in Fig. 1. A set of data based on the ubicomp sensing would be collected via the Sensors. Users control the system using Hypothesis Setting, Sensor Linking and Hypothesis Evaluation interfaces.
Hypothesis setting is based on the form `if I do X then I will see e ect Y over time period Z'. The three parameters of X, Y and Z need to be set using the hypothesis setting interface (Fig. 1. b) and the values of X and Y will be collected over time period Z. For example, the parameters in our scenario's hypothesis are activity level (X), blood pressure (Y) and 6 months (Z).
To create user models and hypothesis, personis [
The goal of this research is de ning a new approach of personal informatics based on ubicomp sensing to achieve long term goals such as being healthier. An architecture is proposed to support personal health hypothesis evaluation. The next steps are to implement this infrastructure and assess how people use it.