Difference between revisions of "Balance Board"

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| caption        = Balance Board
 
| caption        = Balance Board
 
| manuals      = {{bulleted list
 
| manuals      = {{bulleted list
       | [[:File:Capture.JPG|Technical Design]]
+
       | [https://surfdrive.surf.nl/files/index.php/s/ECwhP2Hj5HhQdyS Technical Design]
       | [[Media:SOP_1_BalanceboardCalibration.pdf|Balance Board Calibration Manual]] (pdf)
+
       | [https://surfdrive.surf.nl/files/index.php/s/ECwhP2Hj5HhQdyS Balance Board Manual]] (pdf)
      | [[Media:SOP_2_BalanceBoardBaseline.pdf|Balance Board Baseline Manual]] (pdf)
 
      | [[Media:SOP_3_InstructionPosture.pdf|Instruction Posture Manual]] (pdf)
 
 
   }}
 
   }}
 
}}
 
}}
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===National Instruments===
 
===National Instruments===
[[File:Capture2.JPG|frame|left|300px|National Instruments settings]]<br clear=all>
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[[File:Capture2.JPG|thumb|left|600px|National Instruments settings]]<br clear=all>
  
 
==Usage==
 
==Usage==

Latest revision as of 09:48, 31 January 2019

Balance Board
BalanceBoard1.jpg
Balance Board
Manuals

A balance board(force platform) is commonly used in motor control labs and neurologic clinics. They essentially consist of a set of finely calibrated scales, measuring mechanical forces. The pattern of forces can be used to derive body position, at a high spatial and temporal resolution.


Features

There are several boards specified up to 1M2 and 0,5M2 with a sub-millimeter spatial resolution and a 200 hz temporal resolution.

A typical balance board records at a high spatial and temporal resolution. Regarding spatial resolution: a platform can detect changes from a few sub-millimeters (freezing) to at least 500 centimeter (forward or backward steps). The platform records reliably over four vertical forces. Regarding temporal resolution: the signals are typically sampled at 200 Hz. Even though the system allows even higher sampling rates, in practice 100 Hz is sufficient.

The pressure sensors derive directly from the wii balance board. Each sensor has a maximum pressure of 120Kg. In-house electronics is build to get a clean amplification from the sensors. A National instruments card, USB-6221, takes care of the A/D conversion and connects with usb to a pc. The force plate can be integrated into existing systems for stimulus presentation and for recording bodily signals such as EEG, EMG and heart rate. In practice, this means that the systems are time-locked within millisecond accuracy.


Configuration

National Instruments

National Instruments settings


Usage

Neurobs Presentation

 1sub runtrials_national begin
 2
 3	# The dio_device will setup NI-DAQmx device number 1 "Dev1"
 4	dio_device card = new dio_device(ni_dio_device, 1, 0 );
 5	#int id = card.acquire_analog_input( "MyVoltageOutTask" );
 6	int id1 = card.acquire_analog_input( "ForceMeasurement,Voltage_0" );
 7	int id2 = card.acquire_analog_input( "ForceMeasurement,Voltage_1" );
 8	int id3 = card.acquire_analog_input( "ForceMeasurement,Voltage_2" );
 9	int id4 = card.acquire_analog_input( "ForceMeasurement,Voltage_3" );
10	count_old = response_manager.total_response_count();
11	loop
12	until false
13	begin
14		if response_manager.total_response_count() > count_old then
15			count_old = response_manager.total_response_count();
16			calibrate_board = true;
17		end;
18		
19		message_scale[1] = round(round(card.read_analog( id1, 1000.0 ),6) * 1000.0, 0);
20		message_scale[2] = round(round(card.read_analog( id2, 1000.0 ),6) * 1000.0, 0);
21		message_scale[3] = round(round(card.read_analog( id3, 1000.0 ),6) * 1000.0, 0);
22		message_scale[4] = round(round(card.read_analog( id4, 1000.0 ),6) * 1000.0, 0);
23		
24		if calibrate_board then
25			zero_scale_left_up    = message_scale[left_up];
26			zero_scale_left_down  = message_scale[left_down];
27			zero_scale_right_up   = message_scale[right_up];
28			zero_scale_right_down = message_scale[right_down];
29			calibrate_board = false;
30		end;
31		
32message_scale[left_up]    = message_scale[left_up] - zero_scale_left_up;
33		message_scale[left_down]  = message_scale[left_down] - zero_scale_left_down;
34		message_scale[right_up]   = message_scale[right_up] - zero_scale_right_up;
35		message_scale[right_down] = message_scale[right_down] - zero_scale_right_down;
36		t_scale11.set_caption(string(message_scale[left_up]));
37		t_scale11.redraw();
38		t_scale22.set_caption(string(message_scale[left_down]));
39		t_scale22.redraw();
40		t_scale33.set_caption(string(message_scale[right_up]));
41		t_scale33.redraw();
42		t_scale44.set_caption(string(message_scale[right_down]));
43		t_scale44.redraw();
44		
45		pos_dot_x = (message_scale[right_up] + message_scale[right_down]) - message_scale[left_up] + message_scale[left_down]);
46		pos_dot_y = (message_scale[left_up] + message_scale[right_up]) - message_scale[left_down] + message_scale[right_down]);
47		p_balance.add_part( balance_pos, (pos_dot_x * 1.0), (pos_dot_y * 1.0));
48		t_coord.set_caption(string(pos_dot_x)+","+string(pos_dot_y));
49		t_coord.redraw();
50		
51		p_balance.present();
52		p_balance.remove_part( 8 );
53	end;
54	card.release_analog_input( id1 );
55	card.release_analog_input( id2 );
56	card.release_analog_input( id3 );
57	card.release_analog_input( id4 );			
58end;

Python

 1from PyDAQmx import Task
 2from PyDAQmx.DAQmxConstants import *
 3from PyDAQmx.DAQmxTypes import *
 4import numpy
 5import msvcrt
 6import time
 7
 8times = []
 9try :
10    freq = 100.0 # Hz
11    numinputs = 4
12
13    analog_input = Task()
14    read = int32()
15    timer= time.clock()
16    running = True
17
18    data = numpy.zeros((numinputs,), dtype=numpy.float64)
19
20    #DAQmx Configure Code
21    analog_input.CreateAIVoltageChan("Dev1/ai0:%i" % (numinputs - 1), None, DAQmx_Val_RSE, -10.0,10.0,DAQmx_Val_Volts,None)
22    #analog_input.CfgInputBuffer(0)
23    #analog_input.CfgSampClkTiming("",freq,DAQmx_Val_Rising,DAQmx_Val_ContSamps,1000)
24
25    analog_input.StartTask()
26    datalist = []
27    while running:
28        #DAQmx Start Code
29        
30    
31        
32        timeBeforeRead = time.clock()
33        analog_input.ReadAnalogF64(-1,10.0,DAQmx_Val_GroupByChannel,data,numinputs*2,byref(read),None)
34        ser.write('S')
35        line = ser.readline()
36
37        time.sleep((1 / freq) - (time.clock()- timeBeforeRead))
38        
39        times.append(timeBeforeRead - time.clock())
40       
41  
42        if msvcrt.kbhit():
43            running = False
44        
45
46finally :
47    print "Stop"
48    t = numpy.array(times)
49    deviation = numpy.mean(abs(t - numpy.mean(t)))
50    maxdeviation  = max(abs(t-numpy.mean(t)))
51    
52    print numpy.mean(t), deviation , maxdeviation 
53   
54
55    analog_input.StopTask();


See Also