1. Remote daily activity of Parkinson’s disease patients:
the Akinesia assessment
Matteo Pastorino*1, Laura Pastor-Sanz*2, Maria Teresa Arredondo*3, Jorge Cancela*4, Francisco del Pozo Guerrero5,
Federico Villagra§6, Maria A. Pastor§7
*
Life Supporting Technologies, ETSIT- UPM
Avda. Complutense 30, Madrid, Spain
1
mpastorino@lst.tfo.upm.es
2
lpastor@lst.tfo.upm.es
3
mta@lst.tfo.upm.es
4
jcancela@lst.tfo.upm.es
Center of Biomedical Technology, UPM
#
Campus Montegancedo, Pozuelo de Alarcón, Madrid, Spain.
5
francisco.delpozo@ctb.upm.es
§
Center for Applied Medical Research, University of Navarra
Avda. Pío XII 55, Pamplona, Spain
6
fvillagra@unav.es
7
mapastor@unav.es
Abstract— The aim of this paper is to describe and present the drugs for the treatment of PD, and levodopa appears most
architecture and assessment of Akinesia in Parkinson’s disease suitable for physiological treatment [4].
(PD) patients using wireless, wearable accelerometers. The Among the symptoms ameliorated by brain dopamine
current work is related to a specific module of the PERFORM replacement, akinesia is of particular interest. Akinesia
system, a FP7 project from the European Commission, that
aimed at providing an innovative and reliable tool, able to
includes two distinct motor disorders. One motor disorder of
evaluate, monitor and manage patients suffering from PD. akinesia is bradykinesia, which is defined as slowness of
Previous works indicate a correlation between the lack of movement and clumsiness, is studied by evaluation of
movement of PD patients and the OFF phase. Following this particular movements. Bradykinesia occurs in parallel with
approach, PERFORM system uses the Akinesia assessment, rigidity and impaired skilled motor performance in PD
combined with the output provided by the developed modules patients and is considered a secondary akinesia. The other
related to other PD symptoms (such as bradykinesia and motor disorder of akinesia is hypokinesia, defined as absence
dyskinesia), in order to automatically discriminate ON and OFF of movement. This is a condition in which any automatic
periods in PD patients. movement or action, including gestures, blinking or
I. INTRODUCTION swallowing actions are limited and their frequency decreases,
although the elemental motor functions are maintained and
Idiopathic Parkinson´s disease (PD) is a movement can be performed voluntarily. Hypokinesia may be the
disorder characterised by the triad of bradykinesia, tremor at essential feature of PD and might be labelled primary akinesia
rest and muscular rigidity which results from a decreased [4]. Hypokinesia is not dominant at early stages of the disease,
dopaminergic tone in the motor portions of the putamen [1]. but becomes prominent with the disease progression. It is not
These motor features, which are the principal sources of linked to the severity of rigidity, tremor, and gait dysfunction.
disability, are accompanied by non-motor issues as depression, It can be considered to be simply an idle state in which
anxiety, autonomic dysfunction, sleep disorders, and cognitive patients do not move although elemental motor functions are
impairment, which are believed to result from a combination maintained [4]. Hypokinesia is not accompanied by a clear
of dopamine deficiency in the non-motor portions of the decrease in motivation or impaired cognitive function [4].
striatum and more widespread progressive pathologic changes Antiparkinsonian dopaminergic medications such as L-
in the brainstem, thalamus and eventually the cerebral cortex DOPA and dopamine agonists ameliorate motor deficits in PD
[2]. The available anatomical and physiological studies by compensating for the loss of dopamine [5]. Disease
strongly suggest that PD results from dopaminergic progression modifies the response to Levodopa or agonists
population loss in the substantia nigra pars compacta which defining in the patient a pattern of clinical statues of variable
induces basal ganglia dysfunction and neuronal discharge mobility (ON state) and some wearing off periods when the
abnormalities within the entire motor circuit [3]. The lack of medication ceases to be effective and patient suffer disability
dopamine causes the motor disorder of the PD, in particular to perform precise and fast movements (OFF state). Accurate
the cardinal features of bradykinesia and akinesia symptoms. assessment of movement impairment is necessary to ascertain
Levodopa and dopamine agonists are the most important

2. the motor state and monitor response to standard and caregivers. The sensor size is not bigger than a small
experimental therapeutic interventions [6]. matchbox. Sensors on the arms and legs are attached on
This paper describes a solution for the objective detection specially designed elastic Velcro bands, which allow fixation
and assessment of Akinesia in order to better adjust to any wrist or ankle size. The sensors are placed inside an
medication schedules and personalise treatment of Parkinson’s elastic pocket on the band, which secures it firmly on the
disease (PD) patients. The work has been carried out within patient body avoiding motion artefact due to cloth movement.
the framework of PERFORM [8] FP7 European project, The sensor on the trunk is placed within a zipped elastic
partially funded by the EU, which included the development pocket on a vest. The vest is also equipped with Velcro straps
of an intelligent system that integrates a wide range of to firmly adjust the sensor on the patient chest. The selected
wearable sensors (Figure 1) that constantly record the motor design allows the easy wearing and attachment/detachment of
signals of the PD patients. Data acquired are pre-processed by sensors.
advanced knowledge processing methods, and integrated by
fusion algorithms to allow health professionals to remotely
monitor the overall status of the patients, adjust medication
schedules and dosages, and personalise the treatment [9].
II. SYSTEM FOR DATA COLLECTION
The PERFORM project is based on the development of an
intelligent loop system (Figure 5) that seamlessly integrates a
wide range of wearable micro-sensors constantly monitoring
several motor signals of the patients. Personalisation of
treatment occurs through PERFORM‘s capability to keep
track of the timing and doses of the medication and meals that
the patient is taking.
A. Monitoring System
The wearable device used to recording the motor signals Figure 2 - PERFORM system placement
consists of a tri-axial accelerometers’ set used to record the Once the data has been stored in the SD card, the patient
accelerations of the movements at each patient limb, one needs to connect the logger to a PC where the patient unit,
accelerometer and gyroscope (on the belt) used to record body called Local Base Unit (LBU) is responsible for the
movement accelerations and angular rate, and a data logger identification and quantification of the patient symptoms and
(also located on the belt) that receives and stores all recorded the recording of other useful information for the evaluation of
signals in a SD card (Figure 2). Sensors allow the system the patient status.
detecting and quantifying a wide range of symptoms and
measures of Parkinson’s disease patient i.e. tremor, B. Patient Interface
bradykinesia, dyskinesias and freezing of gait. All sensors Emphasis is given to the design of an interface easy to use
transmit data using Zigbee protocol to a logger device, with for the patient, considering the patient motor disabilities and
62.5 Hz sampling rate (16 milliseconds between samples). limited computer familiarity.
The designed interface inherits the look and feel of the
phone dialling pad, and all system choices are based on it.
Figure 3 - Patient Interface Meals Questionnaire
Figure 1 – PERFORM Monitoring System Prototype
The patients use the interface to declare their subjective
Special attention was paid in order to ensure the monitoring estimation of their own status, to gain access to relevant
system usability and an easy placement for the patient and the disease information, to receive instructions on life-style

3. interventions, such as medication and food intake and on the III. SUBJECTS AND PILOTS
execution of tests. Moreover, PD’s patients declare This section describes the evolution of the PERFORM
medication intake information, which is useful for the patient project, the devices used and the procedures followed to
status assessment. collect and process the signals, highlighting the problems
found and the solutions provided during the different phases.
A. Phase I: Data Collection with SHIMMERS
Eight subjects participated in this study, classified into two
different groups: four PD patients and four healthy subjects.
The symptoms were rated by a professional neurologist with
more than 20 years of experience with PD patients. Four
accelerometers were placed on the right and left forearms and
on the right and left calves, with a fifth accelerometer being
placed on the trunk, at the base of the sternum. Motion data
was collected using the SHIMMER platform. SHIMMER is a
small cordless sensor platform designed by Intel® as a
wearable device for healthsensing applications. All sensors
Figure 4 - Patient Interface Medication Questionnaire
provide 3-axis accelerometric signals and large storage and
C. Local Base Unit low-power standards based communication capabilities. They
This submodule processes the patient signals acquired and also provide a Bluetooth protocol capability that allows
detects the targeted patient symptoms (tremor, levodopa SHIMMERs to stream the data to a computer.
induced dyskinesia and off state). For each symptom, a
dedicated submodule processes the relevant signals, detects
the symptom episode and quantifies it into a severity scale
from 1 to 4, according to the UPDRS (Unified Parkinson’s
Disease Rating Scale) scaling for PD patients [7]. Other
features such as duration, frequency and amplitude might also
be provided for further clinician review and system evaluation.
D. Central Hospital Unit
This module exploits the recorded patient information in Figure 6 - SHIMMER Sensor
order to build a patient symptom profile. For each main During the experiment, the accelerometer measurements
symptom (tremor, levodopa induced dyskinesia and on-off were complemented by a reflective marker and a video
states), it produces a patient profile which describes the camera recording system. This complimentary analysis served
patient’s common symptom features. When a new patient as a support tool to validate the data used for this work.
recording is processed, it is compared with the patient
symptom profile. If significant differences are found, it might B. Phase II: Data Collection with ANCO first release trainer
be due to two reasons: either a temporarily patient behaviour classifier
abnormality or a change in the patient profile. In the last case, The data collection in this phase was performed with a
the system checks whether a substantial number of similar network of wireless 3-axis ALA-6g (ANCO, Athens, Greece
situations are identified for the last time period for the specific [11]) sensors, located on the limbs, trunk and belt of the
patient and if that occurs, it creates an alert. patient. During this phase, data were collected on test patients
in a supervised environment, with the collaboration of the
clinic’s medical staff. Patients involved in this phase were
required to be aged between 18 and 85 years old, suffering
from PD, capable of complying with study requirements,
receiving stable dopaminergic treatment and experiencing
motor fluctuations. Dementia, psychosis and significant
systemic diseases (such as cancer) were the exclusion criteria
applied when selecting participants. The data set used in this
study included trials with twenty PD patients, ten in Navarra
(Spain) and ten in Ioannina (Greece). In order to comply with
ethical requirements, all procedures were carried with the
Clinic Institutional Review Board’s permission.
Figure 5 - PERFORM Loop System

4. of the evaluation of the standard clinical protocol. This phase
included trials with twelve patients in Pamplona (Spain) and
twelve patients in Ioannina (Greece).
D. Phase IV: System Evaluation
A group of 25 patients, after assessing the usability of the
PERFORM project, accepted to participate in the study.
Figure 7 - PERFORM Sensors First Release
Each subject performed a supervised protocol both during
good clinical condition (ON status), and during the wearing
off efficiency of the medication (OFF status). The following
protocol tasks were recorded with a video camera and the
sensors twice a day meanwhile the patient was hospitalised.
The patient was requested to lie down in a hospital bed for 5
minutes; to sit down on a chair for 5 minutes in order to Figure 8 - Technical Tests in Modena -Italy
record a possible resting tremor. Then he/she was asked to
stand up from the chair and perform a series of activities: walk During the phase IV, data were collected in an
for a distance of 5 m, open a door to get into the room (could unsupervised environment and with the collaboration of a
be the bathroom), close the door and then open the door, step caregiver during a week. Data were acquired during an eight-
out of the room and close the door again. Then he/she hour daily session in which patients carried out their normal
continued by leaving the hospital room and walking through daily activity. Furthermore, patients involved in this phase,
the corridor for a straight distance of 10 meters. At the end of fulfilled with the age and medical specifications of the
such distance he/she was requested to turn and walk back to previous phase.
the room. Midway he was asked to stop and drink from a glass A standard UPDRS [7] clinical evaluation was performed
of water located on a table. Subsequently the patient was during the first and the last day, in order to compare the output
asked to return to his/her room and sit down on the chair of the system with clinical assessment provided by the doctor.
where another 5 minutes of recordings were completed. Moreover, patients filled in a diary in order to compare their
subjective evaluation about their overall daily status with the
C. Phase 3: Long time recording results of the PERFORM system.
Data collection of phase III was performed with an The protocol was approved by Ethical Committee of
improved version of the devices that includes a wearable and University of Modena in July 2010, and the PERFORM’s
programmable logger that gives a better mobility to the hardware system was approved by the Technical Department
patients and new ALA-6 g accelerometers sensors equipped of the “Nuovo Ospedale Civile S.Agostino-Estense”.
with an external battery that allows longer data collection
sessions. IV. METHODOLOGY
During the phase III, data were collected during a week in A. System description and classification method
an unsupervised environment and with the collaboration of a
caregiver. Data were acquired during an eight-hour daily During the first phase of the PERFORM project, an
session in which patients carried out their normal daily intelligent system, that monitors the motor signals of the
activity. Furthermore, patients involved in this phase, patients, was developed in order to detect the symptoms
complied with the age and medical specifications of the episodes and quantify them into a severity scale ranging from
previous phase. Moreover, two daily standard clinical protocol 0 to 4, according to the UPDRS [7] scale for PD patients. In
sessions were performed during the trials under the particular, this paper presents the results of an algorithm
supervision of a clinician. The neurologist examined the developed in order to measure the Akinesia. Once data are
patients performing the UPDRS [7] protocol twice a day, both stored in the patient device (usually a PC), the LBU
during the ON and OFF stages. Subsequently, the protocol automatically starts the signal process [10].
sessions were video recorded and matched with the data Different modules were created in order to detect and
logger and sensors recordings. During the protocol session the quantify different symptoms as shown in Figure 9.
patients carried out twice a day the following activities: sit, This module assesses the amount of movement of the
read, drink a glass of water and walk for approximately two patient in space for any given period of time. The amount of
minutes. At the end of the day, data were processed using the movement is a metric that is associated with the PD symptom
training set computed in Phase II and the output was akinesia. “Amount of movement” and “Akinesia” are related
compared with the results provided by the clinician, as a result terms. [opposed terms]

5. In particular, combining the information from the activity
recogniser module, which detects whether the patient is
walking or moving his hands, together with the output of the
akinesia one, it is possible to discriminate the ON and the OFF
phase, based on the general level of energy produced by a PD
patient during a short period of time (5 minutes).
In Figure 10 an example of the akinesia computed during a
period of time of 4 hours is shown. The blue area defines the
walking period, while the grey one defines the no-walking
period. The green line indicates the amount of energy
Figure 9 - Signal process schema of LBU produced during a short period of time, while the black line
defines the ON (lower level) and OFF state (upper level),
This symptom has clinical significance upon itself; in fact, according to the patient diary.
it is mentioned in the UPDRS [7] in question 29. The answers In order to analyse the results of the output of the akinesia
to the question though, are related to Bradykinesia, so the module, the mean value is computed during both the ON and
results of Akinesia are directly presented to the doctor, OFF periods.
without any upper level processing being devoted to Akinesia
itself, not in a direct way.
However, it is worth clarifying that the output of this
module will contribute to upper-level processing in an indirect
way. Previous studies in Radboud University, the Netherlands,
also mentioned the positive impact that taking Akinesia into
account has in automatically discriminating ON from OFF
periods in PD patients. The model works by calculating the
energy combining the signals acquired by the sensors worn by
the patients. The measure gives an assessment of the quantity
of movement during a specific time interval. To calculate this,
the signal is split into 5 minute windows, filtered (LPF at 3
Hz) and the energy of the signal is obtained for each window Figure 11 - ON/OFF difference for NO WALKING period
of time, with 50% of overlapping. The resulting energies of For the analysis of the results, two different scenarios are
each sensor are combined by using a weighted sum in order to considered. The first scenario (Figure 11) compares the mean
take into account all the possible combination of sensors. value of the computed akinesia during the periods when the
B. On/Off evaluation using the Akinesia patient is not walking. The green bar identifies the mean value
of the akinesia during the ON period, while the red one
Analysing graphics referring to Akinesia, detected by the represents the mean value of the akinesia during the OFF
PERFORM system by the parameter energy, it is possible to period.
observe a clear relationship between the detected ON-OFF Following the same approach, the second scenario (Figure
phases and the akinesia levels. There is a strong correlation 12) compares the mean value of the computed akinesia during
between the lack of movement of PD patients and the OFF walking periods.
status. Using the akinesia assessment, combined with the
output provided by the developed modules related to other
symptoms (such as bradykinesia and dyskinesia), it is possible
to discriminate ON and OFF periods in PD patients.
Figure 12 - ON/OFF difference for WALKING period
The global evaluation of both scenarios demonstrates that it
is possible to discriminate ON and OFF periods computing the
lack of movement combining the information provided by
different modules of the PERFORM system, in this case the
activity recognizer and the Akinesia module.
Figure 10 – Akinesia computed during a 4 hours recording session

6. In fact, as illustrated in Figure 11 and Figure 12, the
amount of energy produced during the ON stage is higher than
the energy produced during the OFF stage.
V. CONCLUSIONS
The results obtained so far are very promising, since they
indicate that PERFORM is an objective tool, suitable for
clinical practice that will support health professionals in the
diagnosis and follow-up of PD patients and therefore will
contribute to the patients’ quality of life improvement.
The results presented are computed using the recording of
one patient during 4h and are focused only in the akinesia
results as discriminating parameter for the ON – OFF
condition assessment in PD.
Future works will include a more exhaustive analysis using
all the recordings collected during the pilot phases combining
the results of all PERFORM classifier outputs in order to
create a complete profile of patients.
ACKNOWLEDGMENTS
Authors thank the PERFORM consortium for their
contribution to this work, especially the University Clinic of
Navarra, the University of Ioannina and the Nuovo Ospedale
Civile S.Agostino-Estense of Modena.
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