Hierarchical organization of REMPARK system. | |
System architecture overview. | |
Simplified representation of the ACS functionalities. | |
Smartphone connectivity and information flows. | |
Platform functional architecture. | |
Server services. | |
Illustration of the number of professional who filled the questionnaire divided according to their country of origin. Years of clinical practice in PD area are also reported in the average, also in this case individually for each country. Vertical bars represent the standard deviation. | |
Indices of clinical relevance for each PD motor symptoms examined referred to the mild (blue columns), moderate (red columns) and advanced (green columns) PD stages. Vertical bars represent standard errors. | |
Subjective judgment expressed by professionals about the utility of REMPARK system for both improvement and monitoring of motor symptoms. Vertical bars represent standard errors. | |
Design of the experimental visit. | |
Waist sensor. | |
Wrist sensor. | |
Data structure collected from each patient. | |
Outline of the structure defined for the algorithms for detecting symptoms of PD. | |
Scheme of the bradykinesia detection algorithm. | |
(a) The inertial system prototype (9 × 2, Version 6) positioned in a neoprene belt on left lateral side of waist. Acceleration signals obtained from (a) Lumbosecaral point of waist and (b) left lateral side of waist. | |
Data flow for the algorithms implementation. | |
Internal organisation of the sensor unit. | |
Timing for the online algorithms implementation. | |
Power Management block diagram. | |
Sensor unit casing. | |
External components of the sensor unit. | |
Status of the sensor unit. | |
Special belt and REMPARK final sensor. | |
Sequence of interaction of different experiments. a) Participants had to touch the target, which appeared in different sizes, at different positions and surrounded by distractions of different sizes; b) Participants had to slide a rug which appeared in different heights with different spaces to the distractions; c) Participants had to control the water level, by filling the pipette by touching the arrow up until the water reached the green mark; d) Participants had to use the seek bar with a ball as a selector to drag the ball to the boy; scale and mark’s position changed with test progression. | |
Some examples of UI patterns and gestures. | |
Sequence for text input. | |
Screenshots of the home screens: Applications screen (to the left) and Favourites screen (to the right). | |
Screen flow for the ‘My Data’ application. | |
Screenshot of the ‘My Day’ app. | |
a) Initial screen; b) Number indicating the tap counting; c) Custom display of a tap event. | |
Arrow buttons as an alternative to the scroll gesture. | |
Calendar screens: a) Calendar; b) Week list. | |
New/Edit appointment screen. | |
Medication apps screens: a) medication list; b) medication details; c) edit intake. | |
Notification pop-up screen (medication reminder). | |
Examples of visual cueing strategies. | |
REMPARK Auditory Cueing System. | |
Cueing rhythm (beats per minute BPM) and cadence (steps per minute SPM). | |
Pop-Up window for basic control of ACS when it starts automatically. | |
Auditory Cueing System application. | |
Preliminary tests with PD patients for the ACS. | |
Infusion pump to be adapted for a possible use with REMPARK system. | |
Modified pump. | |
PCB general scheme. | |
System operation overview. | |
Connection diagram between the pump and the designed PCB. | |
View of data on a patient from a list. (All appearing data are not real). | |
Protocol screen capture for apomorphine pump alert. | |
Questionnaire’s section detail. | |
Treatment Plan. A patient’s interface view. | |
The server acting as a communication hub interfacing the DMA System. | |
The Web interface architecture. | |
Communication flow of motor symptoms detection and actuation in REMPARK system. | |
Communication flow of non-motor symptoms management and actuation in REMPARK system. | |
Final REMPARK platform (ready for pilots) functional view. | |
REMPARK server in isolated network. | |
Final REMPARK system deployment and used for the pilots. | |
Timing of the methodological study design. | |
Motor states section of the diary filled by one patient during the first day of experimentation. Third row corresponds to the ‘intermediate state’. | |
System Usability Scale. |
Modified Hoehn and Yahr scale | |
Common motor and non-motor fluctuations in PD | |
Technical specifications derived from the user feedback | |
Some important technical requirements for the sensor module | |
Parameters/Measures considered by the ACS | |
General functional requirements of the ACS system | |
Requirements of the smartphone end-user applications | |
Technical requirements for the REMPARK server | |
Compiled requirements for the DMS | |
Sociodemographic data | |
Recorded time of the different motor periods | |
Video recording duration per symptom in the database | |
Summary of motor symptoms per motor phase | |
Dyskinesia algorithm results | |
Bradykinesia algorithm results | |
Tremor algorithm results | |
Freezing of Gait algorithm results | |
Estimated memory usage | |
Estimated processing time | |
Technology watch on mobile applications for PD management | |
Some important interview results | |
User interface design guidelines | |
Mean duration of a single tap for each participant | |
Technology watch on actuators for auditory cueing in Parkinson’s Disease | |
Pre-pilot results on motor state detection | |
Recruitment and follow-up data by participant entity | |
Mental and chronic disease condition of the participants | |
Example of data stored in the REMPARK server | |
Performance analysis of the REMPARK system (some examples) | |
Average results according to the Original diary method and time-ensured method (Strict) | |
Non-motor symptoms selected answers sorted by frequency | |
Results of the cueing systems for participants with severe gait problems | |
Results for the QUEST questionnaire |
μC | Microcontroller |
μSD | Micro Secure Digital |
A2DP | Advanced Audio Distribution Profile |
AAL | Ambient Assisted Living |
ACS | Auditory Cueing System |
ADL | Activity of Daily Living |
AI | Artificial Intelligence |
AIMS | Abnormal Involuntary Movement Scale |
BADL | Basic Activities of Daily Living (e.g. bathing, toileting, feeding, transferring, dressing) |
BAN | Body Area Network |
BPM | Beats per minute |
CDS | continuous dopaminergic stimulation |
CP | Clinical Protocol |
CPU | Central Processing Unit |
CRF | Case Report Form |
DAO | Data Access Object |
DBS | deep brain stimulation |
DG | Design Guideline |
DMA | Direct Memory Access |
DMA | Disease Management Application |
DMS | Disease Management System |
DSM | Diagnostic and Statistical Manual |
DSP | Digital Signal Processor |
EC | Ethical Committee |
EHR | Electronic Health Record |
FES | Functional Electrical Stimulation |
FFT | Fast Fourier Transform |
FOG | Freezing Of Gait |
FP7 | Framework Programme 7 |
GP | General Practitioners |
GUI | Graphical User Interface |
H&Y | Hoehn and Yahr |
HCI | Human-Computer Interaction |
HER | Electronic Health Record |
HTTPS | HyperText Transfer Protocol over SSL |
I/O | Input/Output |
IADL | Instrumental Activity of Daily Living |
IC | form Informed Consent Form |
ICT | Information and Communication Technologies |
IMU | Inertial Measurement Unit |
IQR | Interquartile Range |
JSON | JavaScript Object Notation |
LED | Light Emitting Diode |
LSVT | Lee Silver voice treatment |
MA | Medical Application |
MC | Motor complication |
MDT | Multidisciplinary treatment |
MG | Mobile Gateway |
MIPS | Mega-instructions per second |
MMSE | Mini Mental State Examination |
MS | Milli Seconds |
URL | Uniform Resource Locator |
MS | Motor Symptom |
MVC | Model-View-Controller |
SQL | Standardized Query Language |
MWI | Medical Web Interface |
NE | Non evaluated (state) |
NMC | Non-motor complication |
NMS | Non-motor Symptom |
NMSQ | Non Motor Symptoms Questionnaire |
OECD | Organisation for Economic Co-operation and Development |
PD | Parkinson’s Disease |
PHS | Personal Health System |
PHS | Personalized Health System |
PT | Physical Therapy |
PwP | People with PD |
QoL | Quality of Life |
QoLRH | quality of life related to health |
QUEST | Quebec User Evaluation of Satisfaction with assistive Technology |
RBD | REM sleep behaviour disorder |
RBF | Radial Basis Function |
RCS | REMPARK Central Server |
RE | Rule Engine |
REM | rapid eye movement |
RFCOMM | Radio Frequency Communication |
SP | Subcutaneous Pump |
SPM | Steps per minute |
SUS | System Usability Scale |
TSN | Transaction Sequence Number |
UI | User Interface |
UPDRS | Unified Parkinson’s Disease Rating Scale |
UX | User eXperience |
Scale | Description |
1.0 | Unilateral involvement only |
1.5 | Unilateral and axial involvement |
2.0 | Bilateral involvement without impairment of balance |
2.5 | Mild bilateral disease with recovery on pull test |
3.0 | Mild to moderate bilateral disease; some postural instability; physically independent |
4.0 | Severe disability; still able to walk or stand unassisted |
5.0 | Wheelchair bound or bed ridden unless aided |
Motor | Non-motor |
OFF dystonia |
Requirement Heading | Requirement Description |
Symptom detection | The system must be able to detect at least the following symptoms: “reduced walking speed”, “small steps”, “freezing of gait”, “dyskinesia”, “bradykinesia” and “falls”. |
Patient interface | The user interface in the mobile gateway must be operated by a PD patient in any stage of PD. |
Symptom mitigation | The system must provide auditory cueing upon detection of “reduced walking speed”, “small steps” and “freezing of gait” symptoms. |
Requirement Heading | Requirement Description |
Structure | The sensor module must contain a sensor unit placed in the patient’s waist and a sensor unit placed in the patient’s wrist. |
Size – waist sensor unit | The dimensions of the waist sensor unit must be smaller than 150×70×30 mm. |
Size – wrist sensor unit | The dimensions of the wrist sensor unit must be smaller than 80×70×30 mm. |
Weight – waist and wrist sensor units | The weight of the sensor units must be low (around 200 g. for the waist unit and 150 g. for the wrist one) |
Battery capacity | The battery on the sensor units must permit a normal continuous operation for at least 8 hours. |
Operation – waist and wrist sensor units | The sensor units must be turned on/off using a single button. |
User interface | The sensor unit must use a single led to display its state. |
Communication | The sensor must be able to establish a wireless link with the mobile gateway. This requirement is only for the operative part and not used during the database construction phase. |
Communication – additional specs | The waist and wrist sensors must be able to send to the mobile gateway its battery status. The waist sensor must be able to send to the mobile gateway data containing indicators for the following movement patterns: stride length, gait speed, bradykinesia, falls, dyskinesia and FOG. |
Communication – security | The data sent by the waist and wrist sensor units to the mobile gateway must be encrypted. |
Sensors – waist sensor unit | The waist sensor unit must contain a triaxial accelerometer, a triaxial gyroscope and a compass. |
Sensors – wrist sensor | The wrist sensor unit must contain a triaxial accelerometer. |
Data sampling rate | The waist sensor unit must be able to sample data from the sensors with a frequency of at least 40 Hz. The wrist sensor unit must be able to sample data from the sensors with a frequency of at least 20 Hz. It must be noted that during the Database construction, used frequency was higher (200 Hz for the waist sensor and 80 Hz for the wrist sensor). |
Data processing | The waist sensor unit must contain a data processing unit able to calculate indicators for the following movement patterns: stride length, gait speed, bradykinesia, falls, dyskinesia and FOG. The wrist sensor unit must contain a data processing unit able to calculate indicators for the following movement patterns: tremor. |
Comfort | The parts of the sensor unit in contact with the patient’s skin must be constructed with a biocompatible material. |
Battery certification | The Li-ion batteries used in the sensor module must have test certificate according to standard UL 1642. |
Battery charger certification | The battery chargers used for the sensor module must have a test certificate demonstrating compliance with IEC 60950. |
Parameter/Measure | Description |
Bradykinesia | Slow movements, slow walk |
FOG episodes | Transient period in which gait is halted. |
Requirement Heading | Requirement Description |
Cueing type | ACS must provide cueing automatically, in a self-adaptive, non-continuous way, taking into account the specific needs of the patient in each situation. |
Operation mode | Cueing must operate only when the patient is walking. |
System interaction | ACS must be able to work in real time, together with the feedback provided by sensors. |
Functional requirements | ACS must be able to detect a bradykinetic gait based on walking speed, stride length and the occurrence of FOG episodes, as measured by movement sensors. |
Stimulus type | ACS must provide stimulus in the form of sounds. |
Sound rhythm | Sounds must pace both left and right footfalls. |
Alerts | ACS must be able to provide voice recordings with alerts and instructions, when required. |
Configurability | ACS must be able to program the activation and deactivation of sound stimulus at the adequate times/situations. |
Adaptation | ACS must be able to automatically adapt the rhythm of cues (sound stimulus) to the specific needs of each patient in each situation. |
Evaluation and Rating | ACS must be able to constantly evaluate the effect of cueing on the patient and to enable the patient to rate the cueing session. |
Requirement Heading | Requirement Description |
Questionnaires | The smartphone must enable the user to answer medical questionnaires sent by the doctor. |
User answers | The smartphone must enable the user to answer specific prompts to validate alerting detected situations. |
User input | The smartphone should enable the user to input routine information such as the time of intake of the medications, quantity and quality of the sleep or other information. |
Actuators | The smartphone should enable the user to adjust the behaviour of the auditory cueing. |
Requirement Heading | Requirement Description |
Service | Server must expose some public services so that the Mobile Gateway, the Rule Engine and the Professional Application can access the generated data. |
Service | Server must provide services that are able to store and extract for each specific patient. |
Measures | Server must provide a service to store measures which will be used by the Mobile Gateway, Rule Engine and the Professional’s application. |
Measures | New measures must be able to be added in a simple fashion. |
Getting Measures | Server must provide a service that allows receiving measures and is accessible by the Mobile Gateway, Rule Engine and Professional Application. |
Alerts | Server must provide a service to notify about alerts which will be used by the Mobile Gateway, Rule Engine and the Professional’s application. |
Alerts | New alerts must be able to be added in a simple fashion |
Storing Alerts – Mobile Gateway |
|
Storing Alerts – Rule Engine |
|
Requirement Heading | Requirement Description |
BAN data | DMS will store all data from the BAN. |
Medical monitoring | DMS will monitor medical aspects of the patient. |
Technical monitoring | DMS will monitor technical aspects of the patient regarding the REMPARK project. |
Alerts | DMS will raise alerts when information about irregular behaviour or measurement will come from the gateway. |
Questionnaires | DMS will allow managing questionnaires. |
Treatment plan | The treatment plan will be created in the DMS. |
Data integrity | No data could be deleted from the database. |
Monitoring interface | The DMS will have a monitoring interface. |
Data interface | The DMS will have an interface for showing patient’s data. |
Website | The DMS will have a patient personal website. |
Reports | The DMS will be able to publish reports. |
Age (Mean ± SD) | 68 (7.9) |
Gender | |
Female | 36 (39.1%) |
Male | 56 (60.9%) |
Marital Status | |
Single | 5 (5.4%) |
Married/partner | 74 (80.5%) |
Widowed | 8 (8.7%) |
Separated/divorced | 5 (5.4%) |
Motor Phase | Time Recorded (hours) |
ON | 163 |
OFF | 111 |
Intermediate | 72 |
Dyskinesia | Bradykinesia | FOG | Tremor | TOTAL | |
Video | 8,10 h | 15,78 h | 2,45 h | 5,60 h | 31,92 h |
Tablet-PC | 62,82 h | 31,82 h | 2,96 h | 45,82 h | 143,43 h |
Total | 70,93 h | 47,60 h | 5,41 h | 51,42 h | 175,36 h |
On (minutes) |
Off (minutes) |
Intermediate (minutes) |
Motor Phase Not Available |
TOTAL (minutes) | ||||||
Video | Tablet | Video | Tablet | Video | Tablet | Video | Tablet | Video | Tablet | |
Dyskinesia | 355 | 2500 | 28 | 431 | 18 | 712 | 85 | 126 | 486 | 3769 |
Bradykinesia | 50 | 122 | 790 | 1394 | 25 | 308 | 81 | 85 | 947 | 1909 |
FOG | 21 | 33 | 113 | 76 | 7 | 36 | 6 | 34 | 147 | 178 |
Tremor | 94 | 789 | 224 | 1200 | 15 | 680 | 2 | 80 | 336 | 2749 |
Total | 520 | 3444 | 1155 | 3100 | 65 | 1737 | 174 | 325 |
Type of Choreic Dyskinesia |
Num. of Patients with This Type of Choreic Dyskinesia | Equal Weight per Minute | |||
Severity | Body Part | Specificity (%) | Sensitivity (%) | Total Minutes | |
Weak | Trunk | 16 | 95 | 78 | 953 |
Strong | Trunk | 4 | 95 | 100 | 895 |
Weak | No-trunk | 32 | 95 | 39 | 1110 |
Strong | No-trunk | 7 | 95 | 90 | 917 |
Specificity | Sensitivity | PPV | NPV |
81% | 88% | 89% | 84% |
RBF+Freq. | Lin.+Freq. | RBF+All | Lin.+All | |
Sensitivity (holdout) | 100,00% | 100,00% | 100,00% | 90,00% |
Specificity (holdout) | 98,50% | 99,50% | 99,30% | 97,20% |
Data Usage (holdout) | 57,70% | 41,10% | 42,00% | 82,10% |
Sensitivity (test) | 97,30% | 91,00% | 98,10% | 92,10% |
Specificity (test) | 96,90% | 99,00% | 98,60% | 97,50% |
Data Usage (test) | 55,50% | 40,80% | 42,00% | 79,90% |
Geometric Mean (test) | 97,10% | 94,90% | 98,40% | 94,80% |
Accuracy (test) | 96,90% | 98,60% | 98,60% | 97,30% |
Kernel | RBF | Linear | RBF | Linear |
Features | Freq. | Freq. | All | All |
Sensitivity (train) | 100,00% | 92,30% | 100,00% | 92,30% |
Specificity (train) | 100,00% | 100,00% | 100,00% | 100,00% |
Data Usage (train) | 69,60% | 89,10% | 90,60% | 98,60% |
Geometric Mean (train) | 100,00% | 96,10% | 100,00% | 96,10% |
Accuracy (train) | 100,00% | 98,70% | 100,00% | 98,50% |
True Positives | 9 | 8 | 9 | 12 |
False Positives | 0 | 0 | 0 | 0 |
True Negatives | 55 | 82 | 65 | 65 |
False Negatives | 1 | 1 | 1 | 1 |
Sensitivity (test) | 90,00% | 88,90% | 90,00% | 92,30% |
Specificity (test) | 100,00% | 100,00% | 100,00% | 100,00% |
Data Usage (test) | 82,30% | 91,90% | 94,90% | 98,70% |
Geometric Mean (test) | 94,90% | 94,30% | 94,90% | 96,10% |
Accuracy (test) | 98,50% | 98,90% | 98,70% | 98,70% |
Description | Memory Type | Memory Usage (bytes) |
Basic System with window Management and communication | Program Memory | 6,5 KB |
Data Memory | 5 KB | |
Bradykinesia Algorithm Memory Usage | Program Memory | 3,5 KB |
Data Memory | 0,5 KB | |
FoG Algorithm Memory Usage | Program Memory | 3,5 KB |
Data Memory | 0,5 KB | |
Dyskinesia Algorithm Memory Usage (FFT included) | Program Memory | 3,5 KB |
Data Memory | 0,7 KB | |
Filters+FallDetection Algorithm Memory Usage | Program Memory | 1,2 KB |
Data Memory | 0,5 KB | |
SD for Debug purposes Memory Usage | Program Memory | 2,8 KB |
Data Memory | 4,2 KB | |
TOTAL | Program Memory | 20 KB |
Data Memory | 11 KB |
Description | Timing | Time (ms) |
Sampling Frequency | Between Samples | 25 |
Adquisition | Every Sample | 0,014 |
Filters + Fall detection algorithm | Every Sample | 0,0318 |
Windowing time | Between Windows | 1600 |
Feature Extraction | Every Window (max) | 151 |
Bradykinesia Algorithm | Every Window (max) | 55 |
FoG Algorithm | Every Window (max) | 3 |
Dyskinesia Algorithm | Every Window (max) | 3 |
Motor Characteristics | |
IR1 | Bradykinesia can slow repetitive movements. |
IR2 | Rigidity makes interaction more imprecise and slower. |
IR3 | Dyskinesia can make the interaction very difficult. |
IR4 | PD may hinder speech. |
IR5 | Some PwP may experience visual disabilities. |
IR6 | PwP are likely to use the phone while standing still or sitting. |
IR7 | The impact of PD hands’ tremor is limited. |
Cognitive Characteristics | |
IR1 | Short-term memory loss is accentuated on PwP. |
IR2 | Thought is slowed by PD. |
IR3 | Depression and apathy are common in PD. |
IR4 | Dementia cases are often observed on later stages of the disease. |
General Characteristics | |
IR1 | Symptoms significantly vary across different PwP. |
IR2 | Symptoms vary between ON and OFF phases. |
IR3 | The disease progresses differently from person to person. |
IR4 | Autonomy is gradually lost. |
Design Guidelines | |
DG1 | Usetap targets with 14 mm of side. |
DG2 | Use the swipe gesture, preferably without activation speed. |
DG3 | Employ controls that use multiple-taps. |
DG4 | Use drag gesture with parsimony. |
DG5 | Prefer multiple-tap over drag. |
DG6 | Adapt interfaces to the momentary characteristics of the user. |
DG7 | Use high contrast coloured elements. |
DG8 | Select the information to display carefully. |
DG9 | Provide clear information of current location at all times. |
DG10 | Avoid time dependent controls. |
DG11 | Prefer multi-modality over a single interaction medium. |
DG12 | Consider smartphone design guidelines for older adults. |
Involuntary |
Voluntary | |||
Mean | Std. Deviation | Mean | Std. Deviation | |
Participant | of Time (ms) | of Time (ms) | of Time (ms) | of Time (ms) |
1 | 166.62 | 197.38 | 133.19 | 90.64 |
2 | 355.00 | 295.57 | 373.06 | 250.11 |
3 | 322.78 | 481.36 | 241.67 | 217.59 |
4 | 413.53 | 456.89 | 193.50 | 87.46 |
5 | 703.25 | 281.18 | 292.92 | 178.22 |
Patient | REMPARK System Output Selection | Specificity | Sensitivity | VPP | VPN | Correlation | Number of Hours Analysed |
1 | Mode | 0.6 | 0.3 | 0.33 | 0.6 | –0.07 | 8 |
Exact time | 1 | 1 | 1 | 1 | 1 | 8 | |
2 | Mode | 0.91 | 0.71 | 0.71 | 0.90 | 0.62 | 29 |
Exact time | 0.73 | 1 | 1 | 0.54 | 0.7 | 29 |
Medical Partner | Contacted Patients | Included Patients | Lost-Dropout Patients | Completed Protocol |
NUI Galway (Ireland) | 7 | 7 | 1 | 6 |
TEKNON (Spain) | 18 | 15 | 0 | 15 |
FSL (Italy) | 16 | 10 | 0 | 10 |
MACCABI (Israel) | 13 | 12 | 2 | 10 |
Total | 54 | 44 | 3 | 41 |
Condition | Number of Participants (n) | % |
High blood pressure | 15 | 36,6 |
Heart conditions | 3 | 7,3 |
Arthritis, osteoarthritis or rheumatic conditions | 11 | 26,8 |
Back ache | 13 | 31,7 |
Asthma or COPD | 1 | 2,4 |
Diabetes | 10 | 24,4 |
Urinary incontinence | 14 | 35 |
High cholesterol | 12 | 29,3 |
Depression | 9 | 22,5 |
Anxiety disorder | 3 | 7,3 |
Stroke, cerebral embolism, cerebral infarct or cerebral bleeding in the past | 0 | 0 |
Cancer (malignant tumours) | 5 | 12,2 |
Osteoporosis | 2 | 5 |
Thyroid disease | 1 | 2,4 |
Cognition (MMSE) | 29 (Median) | 5 (IQR) |
Information Source | Information Variable | Quantity |
Movement sensor | BRADYKINESIA – NUM STEPS (106) | 56955 |
BRADYKINESIA – BRADY MEAN (107) | 56955 | |
BRADYKINESIA – BRADY STD (108) | 56955 | |
DYSKINESIA – DISK PROBABILITY (110) | 56955 | |
DYSKINESIA – DISK CONFIDENCE (111) | 56955 | |
FOG – MAX_FI (112) | 56955 | |
ACTIVITY – SMA (901) | 56955 | |
ACTIVITY – CADENCE (902) | 56955 | |
Smartphone | BRADYKINESIA (201) | 56955 |
FREEZING OF GAIT (202) | 56955 | |
DYSKINESIA (203) | 56955 | |
TAP RESPONSE TIME MEAN (204) | 99 | |
TAP RESPONSE TIME STD (205) | 99 | |
LAST TAP RESPONSE TIME MEAN (206) | 99 | |
LAST TAP RESPONSE TIME STD (207) | 99 | |
TAP TEST RESULT DECISION (208) | 99 |
Patient Number | ID | Number of Time Intervals of Missing Packets | Average Number of Missing Packets Per Time Interval | Number of Time Intervals > 10 min. |
1 | TEKNON 1 | 1 | 2,67 | 0 |
2 | TEKNON 2 | 18 | 10,55 | 6 |
16 | MACC 1 | 37 | 19,74 | 8 |
24 | FSL 1 | 6 | 3,28 | 0 |
25 | FSL 2 | 11 | 7,64 | 2 |
34 | NUIG 1 | 21 | 20,11 | 10 |
Total pilot average | – | 8,64 | 6,70 | 2,16 |
Validation Method | Average Specificity Per Patient | Average Sensitivity Per Patient | Average Number of Validated Hours Per Patient | Average Number of ON/OFF Monitoring Hours Per Patient |
Original diary | 82% | 57% | 9.73 | 81.25 |
Strict diary | 89% | 98% | 6.42 | 81.25 |
Question Number | Question Text | Positive (n) | Positive (%) |
8 | A sense of urgency to pass urine makes you rush to the toilet | 27 | 69,5 |
9 | Getting up regularly at night to pass urine | 27 | 69,5 |
5 | Constipation (less than 3 bowel movements a week) or having to strain to pass a stool (faeces) | 17 | 41,5 |
12 | Problems remembering things that have happened recently or forgetting to do things | 17 | 41,5 |
15 | Difficulty concentrating or staying focused | 17 | 41,5 |
Added | Difficult to speech | 26 | 63,4 |
Added | Have you had unusually strong urges that are hard to control? Do you feel driven to do or think about something and find it hard to stop (Such gambling, cleaning, use the computer, obsessing about food or sex)? | 2 | 4,9 |
FOG Questionnaire Filter* | n | TUG with Cueing: Average Seconds | TUG without Cueing: Average Seconds | Mean Differences (seconds) | Comment |
Questions4 > 2 | 11 | 24,7 | 27,0 | –2,4 | Ns |
Questions5 & 6 > 2 | 9 | 26,9 | 29,5 | –2,5 | Ns |
Questions4 or 5 or 6 > 2 | 16 | 24,5 | 26,0 | –1,5 | Ns |
Not Satisfied At All |
Not Very Satisfied |
More or Less Satisfied |
Quite Satisfied |
Very Satisfied | ||||||
n | % | n | % | n | % | n | % | n | % | |
Dimensions | 0 | 0 | 3 | 7,3 | 10 | 24,4 | 13 | 32 | 15 | 36,6 |
Weight | 0 | 0 | 2 | 4,9 | 6 | 14,6 | 14 | 34 | 19 | 46,3 |
Ease in adjusting | 1 | 2,4 | 1 | 2,4 | 15 | 36,6 | 11 | 27 | 13 | 31,7 |
Safe | 0 | 0 | 0 | 0 | 7 | 17,1 | 22 | 54 | 12 | 29,3 |
Ease in using | 0 | 0 | 2 | 4,9 | 8 | 19,5 | 22 | 54 | 9 | 22 |
Comfort | 3 | 7,3 | 2 | 4,9 | 11 | 26,3 | 18 | 44 | 7 | 17,1 |
Overall satisfaction | 0 | 0 | 2 | 4,9 | 8 | 19,5 | 19 | 46 | 12 | 29,3 |