ESTHER: a Portable Sensor Toolkit to Collect and Monitor
Total Hip Replacement Patient Data
Juan Jimenez Garcia
Delft University of TechnologyFaculty of Industrial Design Engineering Landbergstraat 15
2628 CE Delft, The Netherlands
J.C.JimenezGarcia@ tudelft.nl
Natalia A. Romero
Delft University of TechnologyFaculty of Industrial Design Engineering Landbergstraat 15
2628 CE Delft, The Netherlands N.A.Romero@tudelft.nl
Simone T. Boerema
Roessingh Research and Development Telemedicine group P.O.Box 310, 7500 AH Enschede, The Netherlandss.boerema@rrd.nl
David Keyson
Delft University of Technology Faculty of Industrial Design EngineeringLandbergstraat 15 2628 CE Delft, The Netherlands D.V.Keyson@tudelft.nl
Paul Havinga
University of Twente Faculty of Electrical, Mathematics and Computer ScienceP.O.Box 217 7500 AE Enschede, The Netherlands
P.J.M.Havinga@utwente.nl
ABSTRACT
Due to the increasing cost of medical care, hospitals are looking at post surgery patients’ home as the primary place for recovery. Unfortunately, this paradigm shift involves difficulties for patients and physiotherapists to manage the expected outcomes. While patients face physical and emotional problems related to the new hip, clinical teams have limited resources to follow patients’ health experiences during their recovery. Mobile technologies for home care provide opportunities to remotely support patients in their rehabilitation process. They are designed to become part of patients’ daily activities, which requires a holistic understanding of the dynamics of post-surgery treatment. Therefore, it is foreseen that requirements to design home care technologies should address clinicians’ needs related to the functional aspects as well as patients’ experiences of home recovery. ESTHER (Experience Sampling for Total Hip Replacement) is a research and design toolkit developed to study Total Hip Replacement (THR) patients’ experiences after surgery and to evaluate design interventions to support patients in the complexity of home recovery. The tool is based on the Experience Sampling Method (ESM) to capture patients’ self report on their recovery process. In an iterative approach the tool gradually added to patients’ psychological reports physical activity using wireless sensor nodes. The first three iterations of ESTHER are described to illustrate the value of situated self-reports and the richness of combining both self-report and sensing techniques as a
holistic approach to understand both behavioral and experiential aspects of home recovery. The experience in conducting situated design research has shown to be valuable in understanding the technical as well as social challenges and opportunities for the research and design community of home health technologies.
Categories and Subject Descriptors
H.5.m. [Information Systems]: Information interfaces and representation (e.g., HCI): Miscellaneous
General Terms
Design, Performance, Reliability, Experimentation.
Keywords
Portable sensor system; recovery; patient data; experience sampling method; field studies; total hip replacement.
1. INTRODUCTION
Osteoarthritis is the most common joint disorder that is normally treated with a Total Hip and Knee Replacement procedure (THR & TKR) [1,2]. The increasing demand of hospital resources and the advances in surgery technology have led to a reduction of in-patient care and shorter hospitalization times. As a consequence, post-operatory recovery is now commonly taking place at patient’s home, which has a direct impact in the frequency and quality of communication between patient and the medical team. Research has found that less frequent contact negatively affects the patient’s experiences during the recovery at home [3]. Patients feel an atmosphere of anxiety as they perceive that they are poorly informed about what is normal or what to expect during recovery. Likewise, physiotherapists may find it difficult to follow the individual’s process of recovery [4]. Moreover, there is Permission to make digital or hard copies of all or part of this work for
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little attention to the psychological needs of patients living with a new hip [2,3]. This result in an incomplete assessment of individual patients’ health progress that goes beyond the functional aspects of recovery, increasing the burden on patients in terms of achieving expected improvements in physical condition [3,5,6].
Recent advances in wireless sensing technology offer novel ways to deliver home healthcare services. Portable body sensors and smartphone applications can be designed to adapt the home as a self-care environment by sensing the user’s physical behavior and emotional states and adapting accordingly to changes. Besides the technical issues of building such technological innovations, users’ needs and desires should be addressed in the design of a supportive technology. Adequate user-interaction, tailored feedback, adaptive and user-friendliness have been identified as critical design factors [7,8].
The development of a supportive sensor system for THR patients that addresses both physical and emotional aspects of recovery involves several challenges that were taken as design steps. The first step was getting acquainted with the wishes and desires of THR’s stakeholders (surgeons, physiotherapist, patients and informal caregivers) in order to define the functional and non-functional characteristics of the system architecture. Second, the context of the home recovery, taking into account patients’ experiences while undergoing a THR recovery process, was examined. The third step involved the challenge of developing a portable sensor system that can collect and monitor patients’ physical behavior and emotional states during recovery, with high demands on reliability and ease of use.
To address these challenges, ESTHER (Experience Sampling for Total Hip Replacement) was developed as an in-situ ecological design research toolkit to understand and explore the above described challenges [9]. ESTHER, an ongoing development project, has been developed in a Design Inclusive Research framework [10] in which three iterations have been already designed and tested in the field. Each of these iterations focused on different phases in the development of a portable sensor system that collects and monitors objective physical activity data and subjective data of the user's emotional state.
From previous work [11,12] it was revealed that existing User Centered Design Methods such as workshops, scenarios and qualitative interviews conducted with THR stakeholders (7 patients, 5 physiotherapists and 9 researchers) were not adequate in capturing patients’ context and experiences during the recovery process. In understanding that THR is a dynamic process that involves important physical and emotional changes overtime, a design toolkit was developed to enable the capturing of patients’ health experiences along the recovery process. The toolkit explores self-reporting mechanisms and the combination of sensing and subjective data analysis to better address patients’ needs during recovery. This toolkit was used as design interventions for home health
technologies, where stakeholders requirements and physical and emotional elements of daily life practices were carefully addressed.
The following sections briefly describe the experiences in developing iteratively and testing in the field ESTHER. The paper is divided in three main sections each one dedicated to one iteration where design rational, technical platform, and in the field validation are described and reflected upon. The paper ends with conclusions and future work.
2. ESTHER 1.0: Exploring patients’
experiences overtime
The first iteration focused on the implementation and validation of a research tool based on Experience Sampling Method (ESM) [12,13] to collect patients’ self-reporting on their recovery experience at home.
2.1 Design rational
Existing medical instruments, such as Western Ontario and Mc-Master Universities osteoarthritis index (WOMAC) or the multi-purpose health survey questionnaire (SF-36), have been developed to evaluate functional progress in specific stages of the recovery process [3]. They offer high validity and reliability but their limited focus on individual experiences provides only single isolated functional values resulting in a low correlation between physical indicators and general progress recovery [3,14].
Since contextual information relating to patient’s affective state and patterns of changes are not investigated by traditional methods, the Experience Sampling Method (ESM) [13], as a means to gain a holistic view of the change process, was chosen. ESM has the ability to engage the user at relevant points in time to collect self-report inputs. This is done by means of prompting them with questions to collect momentary experiences. Supported by mobile technologies, the prompting and self-reported data can be conducted using portable devices such as tablets, smartphones or watches. ESM has been shown to be an effective approach in healthcare related studies, since the method is less susceptible to subject recall errors that other self-report feedback elicitation methods [15, 16].
ESTHER 1.0 was designed as tool to investigate the meaningful experiences of a THR patient. Patient reports regarding their physical and emotional state during the recovery process were aimed to be collected. A fixed prompting protocol of four intervals was designed to cover regular daily activities of a patient: waking up, lunch, tea time, and before going to bed. Fixed times around these activities were agreed a priori with each patient. Each prompt comprised two questions: first an open question “How are you doing”, followed by an open/close question that asked the patient to position themselves in a diagram of eight moods using the Pictorial Mood Reporting Instrument (PMRI) [17], based on Russel’s circumflex model of emotion [18]. The patient must select at least one mood, and maximum two, that they feel represents them at the moment of the prompt, with the option to explain in words their choices.
2.2 Platform
The prompting protocol was designed as a step-by-step questionnaire on a tablet (iPad). The ESM tool was implemented on the iPad as a web-based application running in HTML5, Javascript and php (mysql). All patients’ inputs were logged and sent to a webserver for later analysis. The server processed the prompting protocol as well as the inputs from the participants. Text messages and mood selections were stored in a database identified by participant code, a timestamp and type of question.
2.3 Field study
To explore the sensitivity of the prototype in capturing subjective differences of patients’ experiences overtime, a case study was conducted with 5 THR/TKR patients (3 male, 2 female), recruited from the Department of Orthopaedics of Reinier de Graaf hospital in Delft, The Netherlands. They used the tool during the first two weeks of their recovery at home. This design intervention aimed to get insights into the sensitivity, longitudinal and granularity features of ESTHER 1.0 as an in-situ (timed and situated) capturing tool. Data collection consisted of the self-reports captured during the intervention together with exit interviews where the experience and acceptance of the tool were discussed and specific design aspects were surveyed to identify usability issues. A coding scheme was developed to show how this data was aligned with the determinants of THR recovery found in literature and research analysis: functional, psychological, social, context and general health aspects. The focus lied on the medium, the prompts, the self-reporting possibilities and their motivation to answer the questions.
2.4 Summary of results
Collected data represented two types of reports: experiences over patients’ emotional recovery, based on the moods report, and their experiences over physical recovery, related to the open question ‘how are you doing’. The reports indicated that a recovery could be better understood when both physical and emotional dimensions are connected. These relations have the potential to better explain significant moments in the recovery. It was observed that changes in mood provided better insights into
the physical recovery reported. For example, one patient reported several times that he was experiencing no progress in his recovery. By capturing the feeling of frustration of not being able to do more than what was allowed, a deeper understanding of his reports was possible. His perceived insufficient progress was due to limited patience. Another patient reported difficulties in doing her exercises. Her mood at that moment was anxious because she did not understand whether the pain she was feeling was normal at that stage of the recovery. Therefore her problems with exercises where not related to physical capabilities but a perceived lack of information resulting in her being too cautious in executing the exercises.
The rich data collection of patients’ daily life provided first insights of the potential of ESTHER as a research tool looking beyond the functional. While understanding the usefulness of the in-situ (timed and situated) characteristics of the self-reports, further work was conducted on exploring appropriate input mechanisms to facilitate the in-situ reporting, leading to the next prototype.
3. ESTHER 1.1: Exploring in-situ user’s
input mechanisms
ESTHER 1.1 was designed to explore the use of a wearable input mechanism for patients, to facilitate self-reporting by decreasing the burden of carrying a larger device that hindered their mobility.
3.1 Design rational
During the recovery process patients may be using either crutches or rollators making it hard for them to bring along a tablet device all the time. Additionally, from ESTHER 1.0 it appeared that less mood characters could be sufficient for patients to express their mood; therefore only four characters, that represent the four axes of the circumflex model [18], were selected for this iteration. ESTHER 1.1 was designed with the goal of reducing the burden on the user, by also limiting the open questions to one time at the end of the day. These decisions provided an opportunity to port the interface to a smaller physical display. The challenge was to reconfigure the initial design of ESTHER 1.0 to a watch-based platform (see Figure 2).
Figure 2. ESTHER 1.1. Screens flow. Figure 1. ESTHER 1.0. Mood selection screen
.
3.2 Platform
In support of ESTHER 1.1 the LiveView™ watch was used. This was connected via Bluetooth to an Android smartphone running LiveView software. The 1.3-inch OLED display showed the prompts, followed by four moods to select from. Users could navigate through the prompting and moods by pressing the touch-sensitive buttons on the black frame of the watch.
3.3 Field study
To explore the reliability and usability of this prototype, ESTHER 1.1 was tested for a week with one patient aged 72 and volunteer from a local hospital in Delft, The Netherlands. The patient received a manual that explained how to use the watch and how to solve connection failures with the smartphone. The usability of this tool was evaluated via an exit interview.
3.4 Summary of results
In the interview, the participant reported initial interest in sharing his moods with the system as he was attracted by the novel interaction of the watch. However, overtime he felt discouraged by the actual experience in using the watch. Most of the problems were related to connection failures, between the watch and the smartphone. Due to this, the user had to be additionally instructed to re-connect and pair the watch again with the phone creating a high burden on the patient. Navigation through the screens was also frustrating. The buttons were not responsive enough what affected negatively the experience of mood selection. Looking at the data, the reports captured by the end of the day were sufficiently informative. However, the reported moods could not explain directly a particular problem, as the daily prompts were time based and not context dependent. Problems such as being too passive or being too physically active corresponded to ‘critical moments’ of a day, where if captured and linked to mood reported could better describe patient’s holistic recovery progress. The following iteration aimed to explore a sampling protocol that linked sensing and subjective data to trigger questions only when special events were detected.
4. ESTHER 1.2: exploring context-depended
sampling protocols
In this iteration of ESTHER the sampling protocol aimed to use data from on-body sensors to trigger the mood prompts to link physical and emotional aspects of recovery.
4.1 Design rational
To gain more in-depth information into ‘critical moments’ physical activity monitoring was added to trigger mood reporting. The monitoring system was designed to capture values for physical activity (IMA). Thresholds in physical activity were used to prompt patients about their mood at that moment.
A baseline was set according to medical prescription of a THR patient, whom should have at least 10 minutes of moderated physical activity during the initial two weeks of recovery. Considering that an IMA > 2000 represents
moderated physical activity for a normal person, an IMA > 1500 was set for THR patients. Therefore, if a patient registered 8 to 15 minutes of IMA > 1500 in an hour it was considered as complying with the level of physical activity recommended. Below or above that threshold it was considered a ‘critical moment’.
For the sampling protocol, days were split into twelve blocks of one hour (from 8 am to 8 pm). After every hour the tool checked for critical moments. In case of a critical moment, a prompt was triggered with the question “how do you feel?” and the patient could choose from four moods characters: happy, relaxed, bored and angry (based on the Pictorial Mood Reporting Instrument, PMRI).
4.2 Platform
The sensor platform consisted of a waist mounted activity sensor connected wirelessly to a smartphone. The activity sensor used was a ProMove-3D sensor node developed by Inertia Technology, which was placed on the patient’s hip to provide an IMA value out of a three-dimensional acceleration data with a frequency of 1Hz. The IMA values were collected and transmitted over Bluetooth to a smartphone (HTC) with ESTHER 1.2 installed.
Figure 3. ESTHER 1.2 Welcome and mood prompting screen.
The interface was built using an Android-based application. The software read out the activity data (IMA), stored the values locally and transmitted them hourly to a server that processed the sampling protocol.
4.3 Field study
The goal of the study was to verify the defined thresholds for critical moments and the corresponding sampling protocol in the context of THR patients. In addition, the value of mood states was explored to describe patient’s experience of their recovery in relation to their activity level.
The study was conducted with four participants (3 male, 1 female). They were volunteers from the Department of Orthopaedics of Reinier de Graaf hospital in Delft, The Netherlands. Patients were monitored and prompted during the two weeks after discharge from the hospital. Participants received guidance about the use of the monitoring kit and they were instructed to answer the prompt questions in relation to their recovery.
The data collected was analyzed by extracting the percentage values per hour of IMA indicating critical moments as described above. Both, IMA percentage and mood reports were placed in the plots according to the prompting schedule (see Figure 5). At the end of the study
participants were interviewed to discuss their experience, motivations, benefits and preferences when using the system, as well as future applications of the tool. A survey was used to assess the usability, ease-of-use and usefulness of the system.
Figure 4. 3rd day of physical and mood reports for each participant. Blue bars represent physical activity per hour;
positive mood reports are shown in green (relaxed and happy) and in red the negative moods (bored and angry).
4.4 Summary of results
The field study resulted in an extensive amount of quantitative and qualitative data regarding physical activity and mood reports. In total 50 days of monitoring were analyzed. The data showed that patients hardly ever reached the baseline set for normal level of activity, concluding that IMA > 1500 was too high for this target user. This caused a malfunction in the prompting protocol as prompts were triggered almost every hour because of a too low level of activity. Although it is expected that this hourly prompting would be highly disruptive in a longer study, participants accepted and complied with it during the two weeks of study. The preliminary results were analyzed using visualizations that illustrated the intensity of physical activity per hour of a patient linked with mood reports when available. An example can be seen in Figure 4.
Figure 4 shows the third day of recovery of each patient. Considering that the reported moods were related to patients’ recovery experiences it was observed that moods reports enriched the physical data with subjective information of a patient. Moods varied widely per patient during the same stage of recovery, even when patterns of physical activity were similar. When comparing patients 1 and 2, physical activity was comparable as both presented two peaks of activity around noon and mid afternoon while in the rest of the day activity was low. However their reported mood was clearly different. Similarly, patients that showed hardly any physical activity, like patients 3 and 4, also varied in their reported mood.
The reported moods were also in line with the insights gained from informal discussions and exit interviews, where patients’ personalities and individual cases corresponded to their daily mood overview. Patients 1 and 3 were confident and felt easy with their operation and recovery. Patient 2 struggled with a difficult recovery, and patient 4 was the only female which was more expressive than the male participants.
Regarding reliability of the system the main challenge was the optimization of battery life. Due to the prototype nature of these interventions the system was not fully optimized for long battery life. Despite several efforts to lower the battery consumption and improve bluetooth connectivity, the dataset resulted in shorter periods of data collection per day, than expected. The visualization of plotted data and moods lead to the next and current iteration, ESTHER 1.3, which explores real-time feedback to support patients’ self-awareness and self-reflection during recovery.
5. Conclusions and future work
This paper presents the design trajectory of ESTHER as a tool to investigate in depth THR patients’ experiences of a surgery recovery at home and explore possible technology based design opportunities. This tool opened up an interesting iterative design path to discuss the design of a healthcare system that goes beyond the functional aspects of recovery, as well as the the technical challenges of integrating experiential and contextual aspects of a wireless on-body sensor system for patients’ self-monitor recovery progress. In total 17 THR patients and 5
physiotherapists participated in different group sessions, tests and field trials during the design interventions.
The three iterations presented here, ESTHER 1.0, 1.1, 1.2, were designed as situated design interventions where self-reporting techniques and sensing technologies were introduced into patients’ daily life. The goal was to get insights into the technicalities of monitoring, storing and integrating physiological and subjective/personal data. ESTHER 1.0, showed the value of daily reports to capture emotional factors that could not only describe but also explain people’s behavior. ESTHER 1.1, showed the technical challenges and opportunities of mobile prompting and reporting and the possibilities to minimize the burden on participants by simplifying the daily prompts without loosing richness of their reports. ESTHER 1.2, showed the variations in physical activity behavior and mood reports to profile patients’ behavior and to describe their experiences beyond the functional definition. These insights uncover opportunities of ESTHER to be used as a research design tool to capture information and as a design intervention tool to explore the benefits of increasing patients’ self-awareness and self-monitoring capabilities. However, several challenges were also uncovered regarding technical, research and user related issues. With the next iteration, the aim is to continue exploring the balance between low effort on participant and richness in their self-reports, which addresses various technical, research and user challenges. Firstly, in-situ reporting tools like PMRI [17] will be further developed to simplify self-reports without loosing richness of information. Secondly, adaptive prompting will be further explored to make prompting more significant to patients and reduced unwanted ones. Thirdly, the ecosystem of the tool will be simplified to reduce patients’ burden due to technical failures. Finally, work on analyzing and visualizing both sensing and subjective data sets will be further develop to find interconnections beyond descriptive ones between both data sets.
ESTHER 1.3 as a design intervention aims to explore the value of reporting techniques to empower patients’ daily reflections, increasing self-awareness and ultimately becoming involved in the decisions taken regarding their recovery. Also the added value of self-reports for physiotherapists will be investigated in more depth.
ACKNOWLEDGMENTS
SENIOR project (Sensing Systems for Interactive Home-Based Healthcare and Rehabilitation), is an initiative within the program of economical innovation Pieken in de Delta Oost-Nederland. We thank the Orthopedic Department at Reinier de Graaf Hospital and the participants that volunteered in the user sessions and field trials.
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